diff --git "a/llava-med-gpt-cot/log.txt" "b/llava-med-gpt-cot/log.txt" new file mode 100644--- /dev/null +++ "b/llava-med-gpt-cot/log.txt" @@ -0,0 +1,4502 @@ +2025-09-21 12:08:51 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.3.mlp.fc1.bias', 'visual_projection.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.final_layer_norm.bias', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.11.layer_norm1.weight', 'logit_scale', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_projection.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.v_proj.weight'] +- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model). +- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). +2025-09-21 12:08:51 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.3.mlp.fc1.bias', 'visual_projection.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 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'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_projection.weight', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.v_proj.weight'] +- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model). +- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). +2025-09-21 12:08:51 | INFO | LVLM-Med | projector_type: mlp2x_gelu +2025-09-21 12:08:51 | INFO | LVLM-Med | --------------------------This is version 1.5--------------------- +2025-09-21 12:08:52 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_projection.weight', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'text_model.encoder.layers.10.mlp.fc1.bias', 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'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.1.layer_norm1.bias', 'logit_scale', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 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'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'visual_projection.weight', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.1.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.5.mlp.fc2.bias'] +- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model). +- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). +2025-09-21 12:08:52 | WARNING | transformers.modeling_utils | Some weights of the model checkpoint at /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_projection.weight', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 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'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.5.mlp.fc2.bias'] +- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model). +- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). +2025-09-21 12:08:52 | INFO | LVLM-Med | projector_type: mlp2x_gelu +2025-09-21 12:08:52 | INFO | LVLM-Med | --------------------------This is version 1.5--------------------- +2025-09-21 12:10:29 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:10:30 | INFO | wandb | Current SDK version is 0.16.1 +2025-09-21 12:10:30 | INFO | wandb | Configure stats pid to 2467270 +2025-09-21 12:10:30 | INFO | wandb | Loading settings from /root/.config/wandb/settings +2025-09-21 12:10:30 | INFO | wandb | Loading settings from /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/wandb/settings +2025-09-21 12:10:30 | INFO | wandb | Loading settings from environment variables: {'api_key': '***REDACTED***', 'project': 'llava_med'} +2025-09-21 12:10:30 | INFO | wandb | Inferring run settings from compute environment: {'program_relpath': 'llava/train/train_mem_CoT.py', 'program_abspath': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/llava/train/train_mem_CoT.py', 'program': '/netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/llava/train/train_mem_CoT.py'} +2025-09-21 12:10:30 | INFO | wandb | Applying login settings: {'api_key': '***REDACTED***'} +2025-09-21 12:10:30 | INFO | wandb | Applying login settings: {'api_key': '***REDACTED***'} +2025-09-21 12:10:30 | INFO | wandb | Logging user logs to /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/wandb/run-20250921_121030-p1r96i3q/logs/debug.log +2025-09-21 12:10:30 | INFO | wandb | Logging internal logs to /netscratch/duynguyen/Research/Nghiem_LLaVA-Med/LVLM-Med/wandb/run-20250921_121030-p1r96i3q/logs/debug-internal.log +2025-09-21 12:10:30 | INFO | wandb | calling init triggers +2025-09-21 12:10:30 | INFO | wandb | wandb.init called with sweep_config: {} +config: {} +2025-09-21 12:10:30 | INFO | wandb | starting backend +2025-09-21 12:10:30 | INFO | wandb | setting up manager +2025-09-21 12:10:30 | INFO | wandb | multiprocessing start_methods=fork,spawn,forkserver, using: spawn +2025-09-21 12:10:30 | INFO | wandb | backend started and connected +2025-09-21 12:10:30 | DEBUG | wandb | no default config file found in config-defaults.yaml +2025-09-21 12:10:30 | INFO | wandb | updated telemetry +2025-09-21 12:10:30 | INFO | wandb | communicating run to backend with 90.0 second timeout +2025-09-21 12:10:30 | INFO | wandb | communicating current version +2025-09-21 12:10:31 | INFO | wandb | got version response upgrade_message: "wandb version 0.22.0 is available! To upgrade, please run:\n $ pip install wandb --upgrade" + +2025-09-21 12:10:31 | INFO | wandb | starting run threads in backend +2025-09-21 12:10:31 | INFO | wandb | atexit reg +2025-09-21 12:10:31 | INFO | wandb | redirect: wrap_raw +2025-09-21 12:10:31 | INFO | wandb | Wrapping output streams. +2025-09-21 12:10:31 | INFO | wandb | Redirects installed. +2025-09-21 12:10:31 | INFO | wandb | run started, returning control to user process +2025-09-21 12:10:31 | INFO | wandb | config_cb None None {'vocab_size': 32004, 'hidden_size': 4096, 'intermediate_size': 11008, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-06, 'use_cache': False, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float32', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'is_encoder_decoder': False, 'is_decoder': False, 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Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.9511679410934448 | lossAlign: 0 +2025-09-21 12:10:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.6574366092681885 | lossAlign: 0 +2025-09-21 12:10:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.5970873832702637 | lossAlign: 0 +2025-09-21 12:10:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.317221999168396 | lossAlign: 0 +2025-09-21 12:10:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.2736073732376099 | lossAlign: 0 +2025-09-21 12:10:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.1534721851348877 | lossAlign: 0 +2025-09-21 12:10:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 1.0554574728012085 | lossAlign: 0 +2025-09-21 12:11:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.8838806748390198 | lossAlign: 0 +2025-09-21 12:11:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.8519649505615234 | lossAlign: 0 +2025-09-21 12:11:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.783048152923584 | lossAlign: 0 +2025-09-21 12:11:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.7557874321937561 | lossAlign: 0 +2025-09-21 12:11:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.6419590711593628 | lossAlign: 0 +2025-09-21 12:11:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.6695289015769958 | lossAlign: 0 +2025-09-21 12:11:14 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:14 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5703706741333008 | lossAlign: 0 +2025-09-21 12:11:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5718128085136414 | lossAlign: 0 +2025-09-21 12:11:18 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:18 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5964646935462952 | lossAlign: 0 +2025-09-21 12:11:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.536045491695404 | lossAlign: 0 +2025-09-21 12:11:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.5213927626609802 | lossAlign: 0 +2025-09-21 12:11:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.47501495480537415 | lossAlign: 0 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alpha: 1.0 | decoder_output_loss: 0.34658417105674744 | lossAlign: 0 +2025-09-21 12:11:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.4158901274204254 | lossAlign: 0 +2025-09-21 12:11:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.41520750522613525 | lossAlign: 0 +2025-09-21 12:11:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3676703870296478 | lossAlign: 0 +2025-09-21 12:11:47 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:47 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.42789146304130554 | lossAlign: 0 +2025-09-21 12:11:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.34226617217063904 | lossAlign: 0 +2025-09-21 12:11:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.37958824634552 | lossAlign: 0 +2025-09-21 12:11:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.34855467081069946 | lossAlign: 0 +2025-09-21 12:11:56 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:11:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.38105127215385437 | lossAlign: 0 +2025-09-21 12:11:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3042133152484894 | lossAlign: 0 +2025-09-21 12:12:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.30857399106025696 | lossAlign: 0 +2025-09-21 12:12:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3541082441806793 | lossAlign: 0 +2025-09-21 12:12:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.40640443563461304 | lossAlign: 0 +2025-09-21 12:12:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3309166431427002 | lossAlign: 0 +2025-09-21 12:12:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.31626978516578674 | lossAlign: 0 +2025-09-21 12:12:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3327080011367798 | lossAlign: 0 +2025-09-21 12:12:12 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:12:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3686099350452423 | lossAlign: 0 +2025-09-21 12:12:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3755675256252289 | lossAlign: 0 +2025-09-21 12:12:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3157108426094055 | lossAlign: 0 +2025-09-21 12:12:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3516688346862793 | lossAlign: 0 +2025-09-21 12:12:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:12:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29989275336265564 | lossAlign: 0 +2025-09-21 12:12:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.33311474323272705 | lossAlign: 0 +2025-09-21 12:12:25 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:12:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29506078362464905 | lossAlign: 0 +2025-09-21 12:12:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.30220043659210205 | lossAlign: 0 +2025-09-21 12:12:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.30262309312820435 | lossAlign: 0 +2025-09-21 12:12:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3657159209251404 | lossAlign: 0 +2025-09-21 12:12:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.37524330615997314 | lossAlign: 0 +2025-09-21 12:12:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2916495203971863 | lossAlign: 0 +2025-09-21 12:12:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:12:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.322746217250824 | lossAlign: 0 +2025-09-21 12:12:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3443596065044403 | lossAlign: 0 +2025-09-21 12:12:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:12:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:12:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.31728604435920715 | lossAlign: 0 +2025-09-21 12:12:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29406580328941345 | lossAlign: 0 +2025-09-21 12:12:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.31131240725517273 | lossAlign: 0 +2025-09-21 12:12:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2501942217350006 | lossAlign: 0 +2025-09-21 12:12:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:12:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3101416230201721 | lossAlign: 0 +2025-09-21 12:12:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29337838292121887 | lossAlign: 0 +2025-09-21 12:12:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3258092999458313 | lossAlign: 0 +2025-09-21 12:12:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.30167606472969055 | lossAlign: 0 +2025-09-21 12:12:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26565319299697876 | lossAlign: 0 +2025-09-21 12:12:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3248829245567322 | lossAlign: 0 +2025-09-21 12:13:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.32931438088417053 | lossAlign: 0 +2025-09-21 12:13:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2956738770008087 | lossAlign: 0 +2025-09-21 12:13:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.33594974875450134 | lossAlign: 0 +2025-09-21 12:13:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28479817509651184 | lossAlign: 0 +2025-09-21 12:13:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24963441491127014 | lossAlign: 0 +2025-09-21 12:13:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.32109832763671875 | lossAlign: 0 +2025-09-21 12:13:15 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:13:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2952161729335785 | lossAlign: 0 +2025-09-21 12:13:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3084900975227356 | lossAlign: 0 +2025-09-21 12:13:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:13:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:13:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.297993540763855 | lossAlign: 0 +2025-09-21 12:13:20 | INFO | LVLM-Med | Loss: + temperature: 0 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alpha: 1.0 | decoder_output_loss: 0.34999412298202515 | lossAlign: 0 +2025-09-21 12:13:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2891477346420288 | lossAlign: 0 +2025-09-21 12:13:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3321661651134491 | lossAlign: 0 +2025-09-21 12:13:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2790013551712036 | lossAlign: 0 +2025-09-21 12:13:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29123184084892273 | lossAlign: 0 +2025-09-21 12:13:44 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:13:44 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:13:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2834499776363373 | lossAlign: 0 +2025-09-21 12:13:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2845315635204315 | lossAlign: 0 +2025-09-21 12:13:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.31848087906837463 | lossAlign: 0 +2025-09-21 12:13:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26890358328819275 | lossAlign: 0 +2025-09-21 12:13:52 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:13:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26689600944519043 | lossAlign: 0 +2025-09-21 12:13:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3082411289215088 | lossAlign: 0 +2025-09-21 12:13:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3161540925502777 | lossAlign: 0 +2025-09-21 12:13:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2604062557220459 | lossAlign: 0 +2025-09-21 12:14:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26125746965408325 | lossAlign: 0 +2025-09-21 12:14:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29466497898101807 | lossAlign: 0 +2025-09-21 12:14:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3647829592227936 | lossAlign: 0 +2025-09-21 12:14:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2626829445362091 | lossAlign: 0 +2025-09-21 12:14:09 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:14:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28934335708618164 | lossAlign: 0 +2025-09-21 12:14:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2572067975997925 | lossAlign: 0 +2025-09-21 12:14:13 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:14:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24962018430233002 | lossAlign: 0 +2025-09-21 12:14:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.31807389855384827 | lossAlign: 0 +2025-09-21 12:14:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28461384773254395 | lossAlign: 0 +2025-09-21 12:14:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25747185945510864 | lossAlign: 0 +2025-09-21 12:14:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2651059031486511 | lossAlign: 0 +2025-09-21 12:14:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26443180441856384 | lossAlign: 0 +2025-09-21 12:14:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3012520372867584 | lossAlign: 0 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lossAlign: 0 +2025-09-21 12:14:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.33559396862983704 | lossAlign: 0 +2025-09-21 12:14:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2829301655292511 | lossAlign: 0 +2025-09-21 12:14:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3044890761375427 | lossAlign: 0 +2025-09-21 12:14:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2513650953769684 | lossAlign: 0 +2025-09-21 12:14:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2713286578655243 | lossAlign: 0 +2025-09-21 12:14:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2636461555957794 | lossAlign: 0 +2025-09-21 12:14:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24531805515289307 | lossAlign: 0 +2025-09-21 12:14:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2620145380496979 | lossAlign: 0 +2025-09-21 12:14:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27774888277053833 | lossAlign: 0 +2025-09-21 12:14:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.30408430099487305 | lossAlign: 0 +2025-09-21 12:15:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:15:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:15:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27232682704925537 | lossAlign: 0 +2025-09-21 12:15:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2756989300251007 | lossAlign: 0 +2025-09-21 12:15:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2581176161766052 | lossAlign: 0 +2025-09-21 12:15:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2493710219860077 | lossAlign: 0 +2025-09-21 12:15:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25214719772338867 | lossAlign: 0 +2025-09-21 12:15:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23748186230659485 | lossAlign: 0 +2025-09-21 12:15:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2278308868408203 | lossAlign: 0 +2025-09-21 12:15:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2331109195947647 | lossAlign: 0 +2025-09-21 12:15:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:15:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23909930884838104 | lossAlign: 0 +2025-09-21 12:15:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2614552974700928 | lossAlign: 0 +2025-09-21 12:15:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26417917013168335 | lossAlign: 0 +2025-09-21 12:15:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2824873924255371 | lossAlign: 0 +2025-09-21 12:15:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2616634964942932 | lossAlign: 0 +2025-09-21 12:15:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2622166872024536 | lossAlign: 0 +2025-09-21 12:15:32 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:15:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3087247312068939 | lossAlign: 0 +2025-09-21 12:15:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25112012028694153 | lossAlign: 0 +2025-09-21 12:15:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23813562095165253 | lossAlign: 0 +2025-09-21 12:15:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25630536675453186 | lossAlign: 0 +2025-09-21 12:15:40 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:15:40 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:15:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22772638499736786 | lossAlign: 0 +2025-09-21 12:15:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22669357061386108 | lossAlign: 0 +2025-09-21 12:15:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2574542462825775 | lossAlign: 0 +2025-09-21 12:15:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23143957555294037 | lossAlign: 0 +2025-09-21 12:15:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23559287190437317 | lossAlign: 0 +2025-09-21 12:15:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2525065839290619 | lossAlign: 0 +2025-09-21 12:15:53 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:15:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26250913739204407 | lossAlign: 0 +2025-09-21 12:15:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23924364149570465 | lossAlign: 0 +2025-09-21 12:15:57 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:15:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26356908679008484 | lossAlign: 0 +2025-09-21 12:15:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2551344931125641 | lossAlign: 0 +2025-09-21 12:16:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27046850323677063 | lossAlign: 0 +2025-09-21 12:16:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25900331139564514 | lossAlign: 0 +2025-09-21 12:16:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23755531013011932 | lossAlign: 0 +2025-09-21 12:16:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2522321343421936 | lossAlign: 0 +2025-09-21 12:16:10 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:16:10 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:16:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27463459968566895 | lossAlign: 0 +2025-09-21 12:16:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24802006781101227 | lossAlign: 0 +2025-09-21 12:16:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2990066707134247 | lossAlign: 0 +2025-09-21 12:16:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.281983882188797 | lossAlign: 0 +2025-09-21 12:16:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:16:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2548985481262207 | lossAlign: 0 +2025-09-21 12:16:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2514890730381012 | lossAlign: 0 +2025-09-21 12:16:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2522581219673157 | lossAlign: 0 +2025-09-21 12:16:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22802627086639404 | lossAlign: 0 +2025-09-21 12:16:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:16:28 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:16:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23297858238220215 | lossAlign: 0 +2025-09-21 12:16:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28533172607421875 | lossAlign: 0 +2025-09-21 12:16:32 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:16:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24609999358654022 | lossAlign: 0 +2025-09-21 12:16:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2676434814929962 | lossAlign: 0 +2025-09-21 12:16:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2878809869289398 | lossAlign: 0 +2025-09-21 12:16:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29002898931503296 | lossAlign: 0 +2025-09-21 12:16:40 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:16:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23609162867069244 | lossAlign: 0 +2025-09-21 12:16:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2149525135755539 | lossAlign: 0 +2025-09-21 12:16:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2707935571670532 | lossAlign: 0 +2025-09-21 12:16:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23501794040203094 | lossAlign: 0 +2025-09-21 12:16:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26970282196998596 | lossAlign: 0 +2025-09-21 12:16:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27390530705451965 | lossAlign: 0 +2025-09-21 12:16:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2329111397266388 | lossAlign: 0 +2025-09-21 12:16:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2621961832046509 | lossAlign: 0 +2025-09-21 12:16:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2623666226863861 | lossAlign: 0 +2025-09-21 12:16:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3342446982860565 | lossAlign: 0 +2025-09-21 12:17:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2466716468334198 | lossAlign: 0 +2025-09-21 12:17:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24363510310649872 | lossAlign: 0 +2025-09-21 12:17:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28514087200164795 | lossAlign: 0 +2025-09-21 12:17:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2593131363391876 | lossAlign: 0 +2025-09-21 12:17:09 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:17:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2501181364059448 | lossAlign: 0 +2025-09-21 12:17:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2366119921207428 | lossAlign: 0 +2025-09-21 12:17:14 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:17:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22290867567062378 | lossAlign: 0 +2025-09-21 12:17:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24244031310081482 | lossAlign: 0 +2025-09-21 12:17:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22453142702579498 | lossAlign: 0 +2025-09-21 12:17:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2543691098690033 | lossAlign: 0 +2025-09-21 12:17:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23330402374267578 | lossAlign: 0 +2025-09-21 12:17:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24145548045635223 | lossAlign: 0 +2025-09-21 12:17:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2445271909236908 | lossAlign: 0 +2025-09-21 12:17:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.32346370816230774 | lossAlign: 0 +2025-09-21 12:17:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24622264504432678 | lossAlign: 0 +2025-09-21 12:17:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21682816743850708 | lossAlign: 0 +2025-09-21 12:17:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24437367916107178 | lossAlign: 0 +2025-09-21 12:17:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23441478610038757 | lossAlign: 0 +2025-09-21 12:17:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24853205680847168 | lossAlign: 0 +2025-09-21 12:17:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24887150526046753 | lossAlign: 0 +2025-09-21 12:17:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2334403246641159 | lossAlign: 0 +2025-09-21 12:17:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24273723363876343 | lossAlign: 0 +2025-09-21 12:17:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24441739916801453 | lossAlign: 0 +2025-09-21 12:17:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2551993727684021 | lossAlign: 0 +2025-09-21 12:17:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2261812388896942 | lossAlign: 0 +2025-09-21 12:17:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24831457436084747 | lossAlign: 0 +2025-09-21 12:17:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2781147360801697 | lossAlign: 0 +2025-09-21 12:17:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24887897074222565 | lossAlign: 0 +2025-09-21 12:18:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26018285751342773 | lossAlign: 0 +2025-09-21 12:18:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21023648977279663 | lossAlign: 0 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lossAlign: 0 +2025-09-21 12:18:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25654858350753784 | lossAlign: 0 +2025-09-21 12:18:20 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:18:20 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:18:20 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:18:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2544003129005432 | lossAlign: 0 +2025-09-21 12:18:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2676890194416046 | lossAlign: 0 +2025-09-21 12:18:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22950933873653412 | lossAlign: 0 +2025-09-21 12:18:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.255615770816803 | lossAlign: 0 +2025-09-21 12:18:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26470229029655457 | lossAlign: 0 +2025-09-21 12:18:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.257457435131073 | lossAlign: 0 +2025-09-21 12:18:33 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:18:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2578696012496948 | lossAlign: 0 +2025-09-21 12:18:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27477023005485535 | lossAlign: 0 +2025-09-21 12:18:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:18:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21866941452026367 | lossAlign: 0 +2025-09-21 12:18:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23766255378723145 | lossAlign: 0 +2025-09-21 12:18:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:18:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24986042082309723 | lossAlign: 0 +2025-09-21 12:18:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23747244477272034 | lossAlign: 0 +2025-09-21 12:18:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3510254919528961 | lossAlign: 0 +2025-09-21 12:18:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2253117859363556 | lossAlign: 0 +2025-09-21 12:18:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28353172540664673 | lossAlign: 0 +2025-09-21 12:18:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23765166103839874 | lossAlign: 0 +2025-09-21 12:18:54 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:18:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2210693359375 | lossAlign: 0 +2025-09-21 12:18:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23357056081295013 | lossAlign: 0 +2025-09-21 12:18:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25262847542762756 | lossAlign: 0 +2025-09-21 12:18:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20282436907291412 | lossAlign: 0 +2025-09-21 12:19:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26670563220977783 | lossAlign: 0 +2025-09-21 12:19:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20876704156398773 | lossAlign: 0 +2025-09-21 12:19:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2133789360523224 | lossAlign: 0 +2025-09-21 12:19:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2407425343990326 | lossAlign: 0 +2025-09-21 12:19:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23537303507328033 | lossAlign: 0 +2025-09-21 12:19:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2362871617078781 | lossAlign: 0 +2025-09-21 12:19:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2528245151042938 | lossAlign: 0 +2025-09-21 12:19:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22478090226650238 | lossAlign: 0 +2025-09-21 12:19:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2278556525707245 | lossAlign: 0 +2025-09-21 12:19:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23986652493476868 | lossAlign: 0 +2025-09-21 12:19:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2449796199798584 | lossAlign: 0 +2025-09-21 12:19:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2205497920513153 | lossAlign: 0 +2025-09-21 12:19:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:19:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20678171515464783 | lossAlign: 0 +2025-09-21 12:19:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21527087688446045 | lossAlign: 0 +2025-09-21 12:19:32 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:19:32 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:19:32 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:19:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24501805007457733 | lossAlign: 0 +2025-09-21 12:19:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2327079176902771 | lossAlign: 0 +2025-09-21 12:19:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22182509303092957 | lossAlign: 0 +2025-09-21 12:19:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2754739820957184 | lossAlign: 0 +2025-09-21 12:19:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22573886811733246 | lossAlign: 0 +2025-09-21 12:19:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23217710852622986 | lossAlign: 0 +2025-09-21 12:19:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2880820631980896 | lossAlign: 0 +2025-09-21 12:19:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.196583092212677 | lossAlign: 0 +2025-09-21 12:19:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2410164475440979 | lossAlign: 0 +2025-09-21 12:19:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25290054082870483 | lossAlign: 0 +2025-09-21 12:19:53 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:19:53 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:19:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21681751310825348 | lossAlign: 0 +2025-09-21 12:19:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23305147886276245 | lossAlign: 0 +2025-09-21 12:19:57 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:19:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27153918147087097 | lossAlign: 0 +2025-09-21 12:19:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29681146144866943 | lossAlign: 0 +2025-09-21 12:20:01 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:20:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23033785820007324 | lossAlign: 0 +2025-09-21 12:20:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22663597762584686 | lossAlign: 0 +2025-09-21 12:20:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22775711119174957 | lossAlign: 0 +2025-09-21 12:20:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21981900930404663 | lossAlign: 0 +2025-09-21 12:20:10 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:20:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2324860692024231 | lossAlign: 0 +2025-09-21 12:20:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21097072958946228 | lossAlign: 0 +2025-09-21 12:20:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28249290585517883 | lossAlign: 0 +2025-09-21 12:20:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23617252707481384 | lossAlign: 0 +2025-09-21 12:20:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23416630923748016 | lossAlign: 0 +2025-09-21 12:20:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23932182788848877 | lossAlign: 0 +2025-09-21 12:20:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2593015134334564 | lossAlign: 0 +2025-09-21 12:20:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2031985968351364 | lossAlign: 0 +2025-09-21 12:20:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23613576591014862 | lossAlign: 0 +2025-09-21 12:20:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23431409895420074 | lossAlign: 0 +2025-09-21 12:20:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2192714661359787 | lossAlign: 0 +2025-09-21 12:20:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2502904534339905 | lossAlign: 0 +2025-09-21 12:20:34 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:20:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22367902100086212 | lossAlign: 0 +2025-09-21 12:20:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2384776622056961 | lossAlign: 0 +2025-09-21 12:20:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23807717859745026 | lossAlign: 0 +2025-09-21 12:20:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25551751255989075 | lossAlign: 0 +2025-09-21 12:20:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24729472398757935 | lossAlign: 0 +2025-09-21 12:20:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27159321308135986 | lossAlign: 0 +2025-09-21 12:20:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24373166263103485 | lossAlign: 0 +2025-09-21 12:20:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2218131273984909 | lossAlign: 0 +2025-09-21 12:20:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2250511795282364 | lossAlign: 0 +2025-09-21 12:20:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25974395871162415 | lossAlign: 0 +2025-09-21 12:20:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.32428687810897827 | lossAlign: 0 +2025-09-21 12:20:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.207091823220253 | lossAlign: 0 +2025-09-21 12:21:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2193845510482788 | lossAlign: 0 +2025-09-21 12:21:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26495423913002014 | lossAlign: 0 +2025-09-21 12:21:04 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:21:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24807339906692505 | lossAlign: 0 +2025-09-21 12:21:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2653258740901947 | lossAlign: 0 +2025-09-21 12:21:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2123304158449173 | lossAlign: 0 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0 | alpha: 1.0 | decoder_output_loss: 0.21373257040977478 | lossAlign: 0 +2025-09-21 12:21:24 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:21:24 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:21:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2216341644525528 | lossAlign: 0 +2025-09-21 12:21:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23691575229167938 | lossAlign: 0 +2025-09-21 12:21:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.262299120426178 | lossAlign: 0 +2025-09-21 12:21:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27046412229537964 | lossAlign: 0 +2025-09-21 12:21:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23767003417015076 | lossAlign: 0 +2025-09-21 12:21:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23222488164901733 | lossAlign: 0 +2025-09-21 12:21:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19443832337856293 | lossAlign: 0 +2025-09-21 12:21:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2718266546726227 | lossAlign: 0 +2025-09-21 12:21:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2697305679321289 | lossAlign: 0 +2025-09-21 12:21:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22643981873989105 | lossAlign: 0 +2025-09-21 12:21:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28011050820350647 | lossAlign: 0 +2025-09-21 12:21:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22166498005390167 | lossAlign: 0 +2025-09-21 12:21:50 | INFO | LVLM-Med | Wrong this box: [] 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lossAlign: 0 +2025-09-21 12:22:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1985820084810257 | lossAlign: 0 +2025-09-21 12:22:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2315504550933838 | lossAlign: 0 +2025-09-21 12:22:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24237480759620667 | lossAlign: 0 +2025-09-21 12:22:11 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:22:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21146497130393982 | lossAlign: 0 +2025-09-21 12:22:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22316023707389832 | lossAlign: 0 +2025-09-21 12:22:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2663055956363678 | lossAlign: 0 +2025-09-21 12:22:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2601487338542938 | lossAlign: 0 +2025-09-21 12:22:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26218175888061523 | lossAlign: 0 +2025-09-21 12:22:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2227427363395691 | lossAlign: 0 +2025-09-21 12:22:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23363488912582397 | lossAlign: 0 +2025-09-21 12:22:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24951370060443878 | lossAlign: 0 +2025-09-21 12:22:28 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:22:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22572065889835358 | lossAlign: 0 +2025-09-21 12:22:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20809698104858398 | lossAlign: 0 +2025-09-21 12:22:32 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:22:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24520766735076904 | lossAlign: 0 +2025-09-21 12:22:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27976053953170776 | lossAlign: 0 +2025-09-21 12:22:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23401081562042236 | lossAlign: 0 +2025-09-21 12:22:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25006985664367676 | lossAlign: 0 +2025-09-21 12:22:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2704777419567108 | lossAlign: 0 +2025-09-21 12:22:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22528961300849915 | lossAlign: 0 +2025-09-21 12:22:45 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:22:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2684086263179779 | lossAlign: 0 +2025-09-21 12:22:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.32951632142066956 | lossAlign: 0 +2025-09-21 12:22:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22170551121234894 | lossAlign: 0 +2025-09-21 12:22:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2305663377046585 | lossAlign: 0 +2025-09-21 12:22:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24833287298679352 | lossAlign: 0 +2025-09-21 12:22:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29477646946907043 | lossAlign: 0 +2025-09-21 12:22:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24870185554027557 | lossAlign: 0 +2025-09-21 12:22:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23468296229839325 | lossAlign: 0 +2025-09-21 12:23:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2703215181827545 | lossAlign: 0 +2025-09-21 12:23:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2166099101305008 | lossAlign: 0 +2025-09-21 12:23:06 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:23:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22098475694656372 | lossAlign: 0 +2025-09-21 12:23:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21771515905857086 | lossAlign: 0 +2025-09-21 12:23:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21768534183502197 | lossAlign: 0 +2025-09-21 12:23:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22345572710037231 | lossAlign: 0 +2025-09-21 12:23:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24452941119670868 | lossAlign: 0 +2025-09-21 12:23:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2645167112350464 | lossAlign: 0 +2025-09-21 12:23:18 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:23:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:23:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19163154065608978 | lossAlign: 0 +2025-09-21 12:23:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2069195806980133 | lossAlign: 0 +2025-09-21 12:23:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2235117256641388 | lossAlign: 0 +2025-09-21 12:23:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22810865938663483 | lossAlign: 0 +2025-09-21 12:23:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2222350537776947 | lossAlign: 0 +2025-09-21 12:23:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23111124336719513 | lossAlign: 0 +2025-09-21 12:23:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23220734298229218 | lossAlign: 0 +2025-09-21 12:23:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23345118761062622 | lossAlign: 0 +2025-09-21 12:23:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20316895842552185 | lossAlign: 0 +2025-09-21 12:23:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23363220691680908 | lossAlign: 0 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| alpha: 1.0 | decoder_output_loss: 0.23201888799667358 | lossAlign: 0 +2025-09-21 12:23:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20672616362571716 | lossAlign: 0 +2025-09-21 12:23:56 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:23:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25018706917762756 | lossAlign: 0 +2025-09-21 12:23:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20523495972156525 | lossAlign: 0 +2025-09-21 12:24:00 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:00 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2459883987903595 | lossAlign: 0 +2025-09-21 12:24:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22067031264305115 | lossAlign: 0 +2025-09-21 12:24:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20454853773117065 | lossAlign: 0 +2025-09-21 12:24:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2043776661157608 | lossAlign: 0 +2025-09-21 12:24:08 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2201673984527588 | lossAlign: 0 +2025-09-21 12:24:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20768725872039795 | lossAlign: 0 +2025-09-21 12:24:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3396953344345093 | lossAlign: 0 +2025-09-21 12:24:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23658712208271027 | lossAlign: 0 +2025-09-21 12:24:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2007901817560196 | lossAlign: 0 +2025-09-21 12:24:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2116159200668335 | lossAlign: 0 +2025-09-21 12:24:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23043639957904816 | lossAlign: 0 +2025-09-21 12:24:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2894724905490875 | lossAlign: 0 +2025-09-21 12:24:25 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1944301277399063 | lossAlign: 0 +2025-09-21 12:24:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2449304461479187 | lossAlign: 0 +2025-09-21 12:24:29 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23447681963443756 | lossAlign: 0 +2025-09-21 12:24:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2447165697813034 | lossAlign: 0 +2025-09-21 12:24:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24049119651317596 | lossAlign: 0 +2025-09-21 12:24:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2211814969778061 | lossAlign: 0 +2025-09-21 12:24:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25807663798332214 | lossAlign: 0 +2025-09-21 12:24:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21656878292560577 | lossAlign: 0 +2025-09-21 12:24:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1917809247970581 | lossAlign: 0 +2025-09-21 12:24:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21608354151248932 | lossAlign: 0 +2025-09-21 12:24:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23784375190734863 | lossAlign: 0 +2025-09-21 12:24:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2412051260471344 | lossAlign: 0 +2025-09-21 12:24:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21722795069217682 | lossAlign: 0 +2025-09-21 12:24:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3462918698787689 | lossAlign: 0 +2025-09-21 12:24:54 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:54 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:24:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2517249286174774 | lossAlign: 0 +2025-09-21 12:24:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23642857372760773 | lossAlign: 0 +2025-09-21 12:24:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21681255102157593 | lossAlign: 0 +2025-09-21 12:24:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21916526556015015 | lossAlign: 0 +2025-09-21 12:25:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25457656383514404 | lossAlign: 0 +2025-09-21 12:25:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20383016765117645 | lossAlign: 0 +2025-09-21 12:25:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2437697798013687 | lossAlign: 0 +2025-09-21 12:25:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2247971147298813 | lossAlign: 0 +2025-09-21 12:25:11 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:25:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19865210354328156 | lossAlign: 0 +2025-09-21 12:25:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21088026463985443 | lossAlign: 0 +2025-09-21 12:25:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2168097048997879 | lossAlign: 0 +2025-09-21 12:25:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20531073212623596 | lossAlign: 0 +2025-09-21 12:25:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:25:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23613373935222626 | lossAlign: 0 +2025-09-21 12:25:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2651978135108948 | lossAlign: 0 +2025-09-21 12:25:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23369410634040833 | lossAlign: 0 +2025-09-21 12:25:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18735630810260773 | lossAlign: 0 +2025-09-21 12:25:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23700456321239471 | lossAlign: 0 +2025-09-21 12:25:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22275811433792114 | lossAlign: 0 +2025-09-21 12:25:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23900921642780304 | lossAlign: 0 +2025-09-21 12:25:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20927020907402039 | lossAlign: 0 +2025-09-21 12:25:35 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:25:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.220121368765831 | lossAlign: 0 +2025-09-21 12:25:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2119520604610443 | lossAlign: 0 +2025-09-21 12:25:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25655481219291687 | lossAlign: 0 +2025-09-21 12:25:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2227400243282318 | lossAlign: 0 +2025-09-21 12:25:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20112952589988708 | lossAlign: 0 +2025-09-21 12:25:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21937547624111176 | lossAlign: 0 +2025-09-21 12:25:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:25:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:25:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21865302324295044 | lossAlign: 0 +2025-09-21 12:25:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2135549783706665 | lossAlign: 0 +2025-09-21 12:25:52 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:25:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23074185848236084 | lossAlign: 0 +2025-09-21 12:25:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2632888853549957 | lossAlign: 0 +2025-09-21 12:25:56 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:25:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2716640830039978 | lossAlign: 0 +2025-09-21 12:25:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19828322529792786 | lossAlign: 0 +2025-09-21 12:26:00 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28123560547828674 | lossAlign: 0 +2025-09-21 12:26:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23756363987922668 | lossAlign: 0 +2025-09-21 12:26:04 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24690036475658417 | lossAlign: 0 +2025-09-21 12:26:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.249752476811409 | lossAlign: 0 +2025-09-21 12:26:08 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:08 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2340390533208847 | lossAlign: 0 +2025-09-21 12:26:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1935359686613083 | lossAlign: 0 +2025-09-21 12:26:12 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:12 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21538043022155762 | lossAlign: 0 +2025-09-21 12:26:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2645699679851532 | lossAlign: 0 +2025-09-21 12:26:16 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20810437202453613 | lossAlign: 0 +2025-09-21 12:26:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3017082214355469 | lossAlign: 0 +2025-09-21 12:26:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24674755334854126 | lossAlign: 0 +2025-09-21 12:26:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23632122576236725 | lossAlign: 0 +2025-09-21 12:26:26 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21314851939678192 | lossAlign: 0 +2025-09-21 12:26:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1817716509103775 | lossAlign: 0 +2025-09-21 12:26:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20655666291713715 | lossAlign: 0 +2025-09-21 12:26:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2458392232656479 | lossAlign: 0 +2025-09-21 12:26:35 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:26:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21292057633399963 | lossAlign: 0 +2025-09-21 12:26:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2051202803850174 | lossAlign: 0 +2025-09-21 12:26:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2579612135887146 | lossAlign: 0 +2025-09-21 12:26:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20728708803653717 | lossAlign: 0 +2025-09-21 12:26:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23046134412288666 | lossAlign: 0 +2025-09-21 12:26:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.29399627447128296 | lossAlign: 0 +2025-09-21 12:26:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2229653149843216 | lossAlign: 0 +2025-09-21 12:26:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24561376869678497 | lossAlign: 0 +2025-09-21 12:26:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2170216143131256 | lossAlign: 0 +2025-09-21 12:26:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2040288895368576 | lossAlign: 0 +2025-09-21 12:26:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2284029722213745 | lossAlign: 0 +2025-09-21 12:26:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22160416841506958 | lossAlign: 0 +2025-09-21 12:27:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20183180272579193 | lossAlign: 0 +2025-09-21 12:27:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19280722737312317 | lossAlign: 0 +2025-09-21 12:27:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2427082061767578 | lossAlign: 0 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0 | alpha: 1.0 | decoder_output_loss: 0.19194954633712769 | lossAlign: 0 +2025-09-21 12:27:20 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:27:20 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:27:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19601334631443024 | lossAlign: 0 +2025-09-21 12:27:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23125140368938446 | lossAlign: 0 +2025-09-21 12:27:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21450679004192352 | lossAlign: 0 +2025-09-21 12:27:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24413631856441498 | lossAlign: 0 +2025-09-21 12:27:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20726989209651947 | lossAlign: 0 +2025-09-21 12:27:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2166256606578827 | lossAlign: 0 +2025-09-21 12:27:33 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:27:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21039313077926636 | lossAlign: 0 +2025-09-21 12:27:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2594340741634369 | lossAlign: 0 +2025-09-21 12:27:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21288253366947174 | lossAlign: 0 +2025-09-21 12:27:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23655690252780914 | lossAlign: 0 +2025-09-21 12:27:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21197262406349182 | lossAlign: 0 +2025-09-21 12:27:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21431966125965118 | lossAlign: 0 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temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24294576048851013 | lossAlign: 0 +2025-09-21 12:28:15 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:28:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2005552351474762 | lossAlign: 0 +2025-09-21 12:28:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23949970304965973 | lossAlign: 0 +2025-09-21 12:28:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2262633591890335 | lossAlign: 0 +2025-09-21 12:28:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21132615208625793 | lossAlign: 0 +2025-09-21 12:28:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1895512044429779 | lossAlign: 0 +2025-09-21 12:28:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.31352826952934265 | lossAlign: 0 +2025-09-21 12:28:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22159428894519806 | lossAlign: 0 +2025-09-21 12:28:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22649040818214417 | lossAlign: 0 +2025-09-21 12:28:31 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:28:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2337394654750824 | lossAlign: 0 +2025-09-21 12:28:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2153165489435196 | lossAlign: 0 +2025-09-21 12:28:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25320184230804443 | lossAlign: 0 +2025-09-21 12:28:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20132975280284882 | lossAlign: 0 +2025-09-21 12:28:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.236866757273674 | lossAlign: 0 +2025-09-21 12:28:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19936306774616241 | lossAlign: 0 +2025-09-21 12:28:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20469309389591217 | lossAlign: 0 +2025-09-21 12:28:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2022925168275833 | lossAlign: 0 +2025-09-21 12:28:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22559385001659393 | lossAlign: 0 +2025-09-21 12:28:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1946028470993042 | lossAlign: 0 +2025-09-21 12:28:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2233133763074875 | lossAlign: 0 +2025-09-21 12:28:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21981923282146454 | lossAlign: 0 +2025-09-21 12:28:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22332525253295898 | lossAlign: 0 +2025-09-21 12:28:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3013564646244049 | lossAlign: 0 +2025-09-21 12:29:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21287208795547485 | lossAlign: 0 +2025-09-21 12:29:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.223163902759552 | lossAlign: 0 +2025-09-21 12:29:05 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:29:05 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:29:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2141418606042862 | lossAlign: 0 +2025-09-21 12:29:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28766006231307983 | lossAlign: 0 +2025-09-21 12:29:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20184338092803955 | lossAlign: 0 +2025-09-21 12:29:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20374451577663422 | lossAlign: 0 +2025-09-21 12:29:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2400520145893097 | lossAlign: 0 +2025-09-21 12:29:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25580674409866333 | lossAlign: 0 +2025-09-21 12:29:17 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:29:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2582012414932251 | lossAlign: 0 +2025-09-21 12:29:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21974137425422668 | lossAlign: 0 +2025-09-21 12:29:22 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:29:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20804227888584137 | lossAlign: 0 +2025-09-21 12:29:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.198484867811203 | lossAlign: 0 +2025-09-21 12:29:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18981382250785828 | lossAlign: 0 +2025-09-21 12:29:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.249344140291214 | lossAlign: 0 +2025-09-21 12:29:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18764689564704895 | lossAlign: 0 +2025-09-21 12:29:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2120978981256485 | lossAlign: 0 +2025-09-21 12:29:34 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:29:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2148360162973404 | lossAlign: 0 +2025-09-21 12:29:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21509817242622375 | lossAlign: 0 +2025-09-21 12:29:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21710704267024994 | lossAlign: 0 +2025-09-21 12:29:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1909652203321457 | lossAlign: 0 +2025-09-21 12:29:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:29:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22057944536209106 | lossAlign: 0 +2025-09-21 12:29:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2013007402420044 | lossAlign: 0 +2025-09-21 12:29:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21209608018398285 | lossAlign: 0 +2025-09-21 12:29:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23316307365894318 | lossAlign: 0 +2025-09-21 12:29:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20639759302139282 | lossAlign: 0 +2025-09-21 12:29:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22627988457679749 | lossAlign: 0 +2025-09-21 12:29:55 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:29:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18018320202827454 | lossAlign: 0 +2025-09-21 12:29:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20971626043319702 | lossAlign: 0 +2025-09-21 12:30:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19364038109779358 | lossAlign: 0 +2025-09-21 12:30:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2662707269191742 | lossAlign: 0 +2025-09-21 12:30:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1976219117641449 | lossAlign: 0 +2025-09-21 12:30:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21454603970050812 | lossAlign: 0 +2025-09-21 12:30:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20861394703388214 | lossAlign: 0 +2025-09-21 12:30:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22271278500556946 | lossAlign: 0 +2025-09-21 12:30:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21853667497634888 | lossAlign: 0 +2025-09-21 12:30:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23151516914367676 | lossAlign: 0 +2025-09-21 12:30:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2156054675579071 | lossAlign: 0 +2025-09-21 12:30:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22732113301753998 | lossAlign: 0 +2025-09-21 12:30:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:30:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:30:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.180850088596344 | lossAlign: 0 +2025-09-21 12:30:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2154397964477539 | lossAlign: 0 +2025-09-21 12:30:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2046557068824768 | lossAlign: 0 +2025-09-21 12:30:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21487422287464142 | lossAlign: 0 +2025-09-21 12:30:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25815534591674805 | lossAlign: 0 +2025-09-21 12:30:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19267155230045319 | lossAlign: 0 +2025-09-21 12:30:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20297269523143768 | lossAlign: 0 +2025-09-21 12:30:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2129010111093521 | lossAlign: 0 +2025-09-21 12:30:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24270902574062347 | lossAlign: 0 +2025-09-21 12:30:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23296959698200226 | lossAlign: 0 +2025-09-21 12:30:40 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:30:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1818607896566391 | lossAlign: 0 +2025-09-21 12:30:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1842089742422104 | lossAlign: 0 +2025-09-21 12:30:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21637707948684692 | lossAlign: 0 +2025-09-21 12:30:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20544764399528503 | lossAlign: 0 +2025-09-21 12:30:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:30:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:30:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21349729597568512 | lossAlign: 0 +2025-09-21 12:30:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20542752742767334 | lossAlign: 0 +2025-09-21 12:30:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17653131484985352 | lossAlign: 0 +2025-09-21 12:30:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2452896535396576 | lossAlign: 0 +2025-09-21 12:30:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21295687556266785 | lossAlign: 0 +2025-09-21 12:30:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24661915004253387 | lossAlign: 0 +2025-09-21 12:31:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2767990529537201 | lossAlign: 0 +2025-09-21 12:31:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22939124703407288 | lossAlign: 0 +2025-09-21 12:31:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21552956104278564 | lossAlign: 0 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decoder_output_loss: 0.23258282244205475 | lossAlign: 0 +2025-09-21 12:31:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3433552086353302 | lossAlign: 0 +2025-09-21 12:31:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20353850722312927 | lossAlign: 0 +2025-09-21 12:31:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22738082706928253 | lossAlign: 0 +2025-09-21 12:31:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2441108524799347 | lossAlign: 0 +2025-09-21 12:31:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19466012716293335 | lossAlign: 0 +2025-09-21 12:31:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22686146199703217 | lossAlign: 0 +2025-09-21 12:31:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20656214654445648 | lossAlign: 0 +2025-09-21 12:31:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2150973677635193 | lossAlign: 0 +2025-09-21 12:31:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24363993108272552 | lossAlign: 0 +2025-09-21 12:31:38 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:31:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19793833792209625 | lossAlign: 0 +2025-09-21 12:31:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27146419882774353 | lossAlign: 0 +2025-09-21 12:31:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:31:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23000280559062958 | lossAlign: 0 +2025-09-21 12:31:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 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0.18978774547576904 | lossAlign: 0 +2025-09-21 12:32:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19068129360675812 | lossAlign: 0 +2025-09-21 12:32:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21724362671375275 | lossAlign: 0 +2025-09-21 12:32:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23545517027378082 | lossAlign: 0 +2025-09-21 12:32:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2083711326122284 | lossAlign: 0 +2025-09-21 12:32:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2413635551929474 | lossAlign: 0 +2025-09-21 12:32:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1940559595823288 | lossAlign: 0 +2025-09-21 12:32:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2535833716392517 | lossAlign: 0 +2025-09-21 12:32:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19208389520645142 | lossAlign: 0 +2025-09-21 12:32:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1877187341451645 | lossAlign: 0 +2025-09-21 12:32:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2219744175672531 | lossAlign: 0 +2025-09-21 12:32:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2450161725282669 | lossAlign: 0 +2025-09-21 12:32:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2335348278284073 | lossAlign: 0 +2025-09-21 12:32:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20606820285320282 | lossAlign: 0 +2025-09-21 12:32:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16909125447273254 | lossAlign: 0 +2025-09-21 12:32:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20258021354675293 | lossAlign: 0 +2025-09-21 12:32:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17719131708145142 | lossAlign: 0 +2025-09-21 12:32:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22109898924827576 | lossAlign: 0 +2025-09-21 12:32:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25362375378608704 | lossAlign: 0 +2025-09-21 12:32:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19252412021160126 | lossAlign: 0 +2025-09-21 12:32:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27191469073295593 | lossAlign: 0 +2025-09-21 12:32:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21154862642288208 | lossAlign: 0 +2025-09-21 12:32:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23002786934375763 | lossAlign: 0 +2025-09-21 12:32:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18610522150993347 | lossAlign: 0 +2025-09-21 12:32:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20338737964630127 | lossAlign: 0 +2025-09-21 12:33:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2355450689792633 | lossAlign: 0 +2025-09-21 12:33:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21059229969978333 | lossAlign: 0 +2025-09-21 12:33:05 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:33:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19245299696922302 | lossAlign: 0 +2025-09-21 12:33:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19622071087360382 | lossAlign: 0 +2025-09-21 12:33:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2266002744436264 | lossAlign: 0 +2025-09-21 12:33:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19646382331848145 | lossAlign: 0 +2025-09-21 12:33:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18027907609939575 | lossAlign: 0 +2025-09-21 12:33:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24384380877017975 | lossAlign: 0 +2025-09-21 12:33:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18949857354164124 | lossAlign: 0 +2025-09-21 12:33:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2199816256761551 | lossAlign: 0 +2025-09-21 12:33:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:33:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18318772315979004 | lossAlign: 0 +2025-09-21 12:33:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.304711252450943 | lossAlign: 0 +2025-09-21 12:33:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2291538119316101 | lossAlign: 0 +2025-09-21 12:33:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17347198724746704 | lossAlign: 0 +2025-09-21 12:33:30 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:33:30 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:33:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23457439243793488 | lossAlign: 0 +2025-09-21 12:33:31 | INFO | LVLM-Med | Loss: + temperature: 0 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this box: [] +2025-09-21 12:33:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2002784162759781 | lossAlign: 0 +2025-09-21 12:33:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1835709810256958 | lossAlign: 0 +2025-09-21 12:33:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:33:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:33:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20025546848773956 | lossAlign: 0 +2025-09-21 12:33:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22147665917873383 | lossAlign: 0 +2025-09-21 12:33:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20255614817142487 | lossAlign: 0 +2025-09-21 12:33:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20110614597797394 | lossAlign: 0 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| lossAlign: 0 +2025-09-21 12:34:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18448418378829956 | lossAlign: 0 +2025-09-21 12:34:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1764795184135437 | lossAlign: 0 +2025-09-21 12:34:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.189947247505188 | lossAlign: 0 +2025-09-21 12:34:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20764027535915375 | lossAlign: 0 +2025-09-21 12:34:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18948319554328918 | lossAlign: 0 +2025-09-21 12:34:23 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:34:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18986456096172333 | lossAlign: 0 +2025-09-21 12:34:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21053418517112732 | lossAlign: 0 +2025-09-21 12:34:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:34:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:34:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23280298709869385 | lossAlign: 0 +2025-09-21 12:34:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1982201188802719 | lossAlign: 0 +2025-09-21 12:34:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17587774991989136 | lossAlign: 0 +2025-09-21 12:34:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20698368549346924 | lossAlign: 0 +2025-09-21 12:34:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18642021715641022 | lossAlign: 0 +2025-09-21 12:34:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21683265268802643 | lossAlign: 0 +2025-09-21 12:34:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1990058422088623 | lossAlign: 0 +2025-09-21 12:34:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22260034084320068 | lossAlign: 0 +2025-09-21 12:34:44 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:34:44 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:34:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1933629959821701 | lossAlign: 0 +2025-09-21 12:34:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18929417431354523 | lossAlign: 0 +2025-09-21 12:34:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2085011750459671 | lossAlign: 0 +2025-09-21 12:34:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18010669946670532 | lossAlign: 0 +2025-09-21 12:34:52 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:34:52 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:34:52 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:34:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1999368965625763 | lossAlign: 0 +2025-09-21 12:34:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21042153239250183 | lossAlign: 0 +2025-09-21 12:34:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20711922645568848 | lossAlign: 0 +2025-09-21 12:34:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23068863153457642 | lossAlign: 0 +2025-09-21 12:35:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1967243105173111 | lossAlign: 0 +2025-09-21 12:35:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20849105715751648 | lossAlign: 0 +2025-09-21 12:35:05 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:35:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20340630412101746 | lossAlign: 0 +2025-09-21 12:35:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25630122423171997 | lossAlign: 0 +2025-09-21 12:35:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19229766726493835 | lossAlign: 0 +2025-09-21 12:35:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21706102788448334 | lossAlign: 0 +2025-09-21 12:35:13 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:35:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19210340082645416 | lossAlign: 0 +2025-09-21 12:35:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26456624269485474 | lossAlign: 0 +2025-09-21 12:35:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19603291153907776 | lossAlign: 0 +2025-09-21 12:35:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22252827882766724 | lossAlign: 0 +2025-09-21 12:35:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:35:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23308797180652618 | lossAlign: 0 +2025-09-21 12:35:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19066564738750458 | lossAlign: 0 +2025-09-21 12:35:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18656817078590393 | lossAlign: 0 +2025-09-21 12:35:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19221735000610352 | lossAlign: 0 +2025-09-21 12:35:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21189694106578827 | lossAlign: 0 +2025-09-21 12:35:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18752671778202057 | lossAlign: 0 +2025-09-21 12:35:33 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:35:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1926739513874054 | lossAlign: 0 +2025-09-21 12:35:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19944828748703003 | lossAlign: 0 +2025-09-21 12:35:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19983410835266113 | lossAlign: 0 +2025-09-21 12:35:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18792065978050232 | lossAlign: 0 +2025-09-21 12:35:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1928272396326065 | lossAlign: 0 +2025-09-21 12:35:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21367156505584717 | lossAlign: 0 +2025-09-21 12:35:45 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:35:45 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:35:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19887828826904297 | lossAlign: 0 +2025-09-21 12:35:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1928354799747467 | lossAlign: 0 +2025-09-21 12:35:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18558114767074585 | lossAlign: 0 +2025-09-21 12:35:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19172652065753937 | lossAlign: 0 +2025-09-21 12:35:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19443513453006744 | lossAlign: 0 +2025-09-21 12:35:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19479280710220337 | lossAlign: 0 +2025-09-21 12:35:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20021261274814606 | lossAlign: 0 +2025-09-21 12:35:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21058979630470276 | lossAlign: 0 +2025-09-21 12:36:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22034169733524323 | lossAlign: 0 +2025-09-21 12:36:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16795064508914948 | lossAlign: 0 +2025-09-21 12:36:06 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:36:06 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:36:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19671493768692017 | lossAlign: 0 +2025-09-21 12:36:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22839318215847015 | lossAlign: 0 +2025-09-21 12:36:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18855343759059906 | lossAlign: 0 +2025-09-21 12:36:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18344789743423462 | lossAlign: 0 +2025-09-21 12:36:14 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:36:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17153656482696533 | lossAlign: 0 +2025-09-21 12:36:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19827120006084442 | lossAlign: 0 +2025-09-21 12:36:18 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:36:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1926804929971695 | lossAlign: 0 +2025-09-21 12:36:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19297070801258087 | lossAlign: 0 +2025-09-21 12:36:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1955750733613968 | lossAlign: 0 +2025-09-21 12:36:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20886550843715668 | lossAlign: 0 +2025-09-21 12:36:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17613127827644348 | lossAlign: 0 +2025-09-21 12:36:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2107803374528885 | lossAlign: 0 +2025-09-21 12:36:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18491101264953613 | lossAlign: 0 +2025-09-21 12:36:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22942398488521576 | lossAlign: 0 +2025-09-21 12:36:35 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:36:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15928520262241364 | lossAlign: 0 +2025-09-21 12:36:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17198051512241364 | lossAlign: 0 +2025-09-21 12:36:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17383484542369843 | lossAlign: 0 +2025-09-21 12:36:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23386527597904205 | lossAlign: 0 +2025-09-21 12:36:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1795632541179657 | lossAlign: 0 +2025-09-21 12:36:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2332398146390915 | lossAlign: 0 +2025-09-21 12:36:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19050973653793335 | lossAlign: 0 +2025-09-21 12:36:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2044013887643814 | lossAlign: 0 +2025-09-21 12:36:51 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:36:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15137659013271332 | lossAlign: 0 +2025-09-21 12:36:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16792257130146027 | lossAlign: 0 +2025-09-21 12:36:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19076314568519592 | lossAlign: 0 +2025-09-21 12:36:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2013489156961441 | lossAlign: 0 +2025-09-21 12:37:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20387840270996094 | lossAlign: 0 +2025-09-21 12:37:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17305609583854675 | lossAlign: 0 +2025-09-21 12:37:03 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:37:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1773434281349182 | lossAlign: 0 +2025-09-21 12:37:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17711219191551208 | lossAlign: 0 +2025-09-21 12:37:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.201982319355011 | lossAlign: 0 +2025-09-21 12:37:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17717428505420685 | lossAlign: 0 +2025-09-21 12:37:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21736469864845276 | lossAlign: 0 +2025-09-21 12:37:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19735212624073029 | lossAlign: 0 +2025-09-21 12:37:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17545096576213837 | lossAlign: 0 +2025-09-21 12:37:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21460020542144775 | lossAlign: 0 +2025-09-21 12:37:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18893371522426605 | lossAlign: 0 +2025-09-21 12:37:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18696559965610504 | lossAlign: 0 +2025-09-21 12:37:23 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:37:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18151602149009705 | lossAlign: 0 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0 | alpha: 1.0 | decoder_output_loss: 0.1871694177389145 | lossAlign: 0 +2025-09-21 12:37:40 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:37:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18276430666446686 | lossAlign: 0 +2025-09-21 12:37:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18464970588684082 | lossAlign: 0 +2025-09-21 12:37:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20132218301296234 | lossAlign: 0 +2025-09-21 12:37:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19218935072422028 | lossAlign: 0 +2025-09-21 12:37:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1808832287788391 | lossAlign: 0 +2025-09-21 12:37:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23577356338500977 | lossAlign: 0 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12:38:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19344113767147064 | lossAlign: 0 +2025-09-21 12:38:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1833648979663849 | lossAlign: 0 +2025-09-21 12:38:09 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23091647028923035 | lossAlign: 0 +2025-09-21 12:38:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19250324368476868 | lossAlign: 0 +2025-09-21 12:38:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20041626691818237 | lossAlign: 0 +2025-09-21 12:38:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18679620325565338 | lossAlign: 0 +2025-09-21 12:38:17 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23090419173240662 | lossAlign: 0 +2025-09-21 12:38:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1724541038274765 | lossAlign: 0 +2025-09-21 12:38:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2073202282190323 | lossAlign: 0 +2025-09-21 12:38:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2005980908870697 | lossAlign: 0 +2025-09-21 12:38:25 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18701961636543274 | lossAlign: 0 +2025-09-21 12:38:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18361333012580872 | lossAlign: 0 +2025-09-21 12:38:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1785062998533249 | lossAlign: 0 +2025-09-21 12:38:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18695113062858582 | lossAlign: 0 +2025-09-21 12:38:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16243456304073334 | lossAlign: 0 +2025-09-21 12:38:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.233457550406456 | lossAlign: 0 +2025-09-21 12:38:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2592383921146393 | lossAlign: 0 +2025-09-21 12:38:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1734246462583542 | lossAlign: 0 +2025-09-21 12:38:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19217340648174286 | lossAlign: 0 +2025-09-21 12:38:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17037281394004822 | lossAlign: 0 +2025-09-21 12:38:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18981467187404633 | lossAlign: 0 +2025-09-21 12:38:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15116877853870392 | lossAlign: 0 +2025-09-21 12:38:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20998287200927734 | lossAlign: 0 +2025-09-21 12:38:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21883703768253326 | lossAlign: 0 +2025-09-21 12:38:54 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20729169249534607 | lossAlign: 0 +2025-09-21 12:38:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.191653311252594 | lossAlign: 0 +2025-09-21 12:38:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:38:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18703611195087433 | lossAlign: 0 +2025-09-21 12:38:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2006921023130417 | lossAlign: 0 +2025-09-21 12:39:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23981760442256927 | lossAlign: 0 +2025-09-21 12:39:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21031838655471802 | lossAlign: 0 +2025-09-21 12:39:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1995355635881424 | lossAlign: 0 +2025-09-21 12:39:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24222992360591888 | lossAlign: 0 +2025-09-21 12:39:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17156270146369934 | lossAlign: 0 +2025-09-21 12:39:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28297391533851624 | lossAlign: 0 +2025-09-21 12:39:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17290112376213074 | lossAlign: 0 +2025-09-21 12:39:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1827463060617447 | lossAlign: 0 +2025-09-21 12:39:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18629947304725647 | lossAlign: 0 +2025-09-21 12:39:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2064456343650818 | lossAlign: 0 +2025-09-21 12:39:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1946801245212555 | lossAlign: 0 +2025-09-21 12:39:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21156403422355652 | lossAlign: 0 +2025-09-21 12:39:28 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:39:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20532196760177612 | lossAlign: 0 +2025-09-21 12:39:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2888616621494293 | lossAlign: 0 +2025-09-21 12:39:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.192182719707489 | lossAlign: 0 +2025-09-21 12:39:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21924665570259094 | lossAlign: 0 +2025-09-21 12:39:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:39:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:39:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19369512796401978 | lossAlign: 0 +2025-09-21 12:39:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16645310819149017 | lossAlign: 0 +2025-09-21 12:39:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21295414865016937 | lossAlign: 0 +2025-09-21 12:39:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19572240114212036 | lossAlign: 0 +2025-09-21 12:39:45 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:39:45 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:39:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18440738320350647 | lossAlign: 0 +2025-09-21 12:39:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20055298507213593 | lossAlign: 0 +2025-09-21 12:39:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18469639122486115 | lossAlign: 0 +2025-09-21 12:39:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19066990911960602 | lossAlign: 0 +2025-09-21 12:39:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21343733370304108 | lossAlign: 0 +2025-09-21 12:39:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1907971054315567 | lossAlign: 0 +2025-09-21 12:39:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21642641723155975 | lossAlign: 0 +2025-09-21 12:39:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18977753818035126 | lossAlign: 0 +2025-09-21 12:40:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19168943166732788 | lossAlign: 0 +2025-09-21 12:40:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19697879254817963 | lossAlign: 0 +2025-09-21 12:40:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2275530993938446 | lossAlign: 0 +2025-09-21 12:40:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1892412155866623 | lossAlign: 0 +2025-09-21 12:40:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22853603959083557 | lossAlign: 0 +2025-09-21 12:40:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1961018294095993 | lossAlign: 0 +2025-09-21 12:40:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21192298829555511 | lossAlign: 0 +2025-09-21 12:40:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18617643415927887 | lossAlign: 0 +2025-09-21 12:40:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21190908551216125 | lossAlign: 0 +2025-09-21 12:40:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1986979842185974 | lossAlign: 0 +2025-09-21 12:40:22 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:40:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17339684069156647 | lossAlign: 0 +2025-09-21 12:40:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.27335309982299805 | lossAlign: 0 +2025-09-21 12:40:26 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:40:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 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12:40:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25791996717453003 | lossAlign: 0 +2025-09-21 12:40:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1735912263393402 | lossAlign: 0 +2025-09-21 12:40:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19966135919094086 | lossAlign: 0 +2025-09-21 12:40:47 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:40:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.179888054728508 | lossAlign: 0 +2025-09-21 12:40:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1985800564289093 | lossAlign: 0 +2025-09-21 12:40:51 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:40:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22262342274188995 | lossAlign: 0 +2025-09-21 12:40:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16915886104106903 | lossAlign: 0 +2025-09-21 12:40:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16504980623722076 | lossAlign: 0 +2025-09-21 12:40:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26587557792663574 | lossAlign: 0 +2025-09-21 12:41:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20491844415664673 | lossAlign: 0 +2025-09-21 12:41:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18939919769763947 | lossAlign: 0 +2025-09-21 12:41:04 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:41:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1663045734167099 | lossAlign: 0 +2025-09-21 12:41:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2238585352897644 | lossAlign: 0 +2025-09-21 12:41:08 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:41:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1752004474401474 | lossAlign: 0 +2025-09-21 12:41:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18245120346546173 | lossAlign: 0 +2025-09-21 12:41:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19113761186599731 | lossAlign: 0 +2025-09-21 12:41:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22814291715621948 | lossAlign: 0 +2025-09-21 12:41:16 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:41:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20092138648033142 | lossAlign: 0 +2025-09-21 12:41:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20973500609397888 | lossAlign: 0 +2025-09-21 12:41:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.215891033411026 | lossAlign: 0 +2025-09-21 12:41:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21534840762615204 | lossAlign: 0 +2025-09-21 12:41:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2431311309337616 | lossAlign: 0 +2025-09-21 12:41:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.194516122341156 | lossAlign: 0 +2025-09-21 12:41:29 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:41:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18662545084953308 | lossAlign: 0 +2025-09-21 12:41:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20239387452602386 | lossAlign: 0 +2025-09-21 12:41:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22325101494789124 | lossAlign: 0 +2025-09-21 12:41:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23158609867095947 | lossAlign: 0 +2025-09-21 12:41:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21409399807453156 | lossAlign: 0 +2025-09-21 12:41:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20721231400966644 | lossAlign: 0 +2025-09-21 12:41:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:41:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1862063705921173 | lossAlign: 0 +2025-09-21 12:41:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18293152749538422 | lossAlign: 0 +2025-09-21 12:41:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17381007969379425 | lossAlign: 0 +2025-09-21 12:41:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.183008074760437 | lossAlign: 0 +2025-09-21 12:41:49 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:41:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18685124814510345 | lossAlign: 0 +2025-09-21 12:41:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18849915266036987 | lossAlign: 0 +2025-09-21 12:41:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18245652318000793 | lossAlign: 0 +2025-09-21 12:41:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18699020147323608 | lossAlign: 0 +2025-09-21 12:41:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1981406956911087 | lossAlign: 0 +2025-09-21 12:41:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20974978804588318 | lossAlign: 0 +2025-09-21 12:42:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:42:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:42:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21589000523090363 | lossAlign: 0 +2025-09-21 12:42:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.26583579182624817 | lossAlign: 0 +2025-09-21 12:42:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1973493993282318 | lossAlign: 0 +2025-09-21 12:42:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17996439337730408 | lossAlign: 0 +2025-09-21 12:42:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2228645384311676 | lossAlign: 0 +2025-09-21 12:42:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19551877677440643 | lossAlign: 0 +2025-09-21 12:42:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23055651783943176 | lossAlign: 0 +2025-09-21 12:42:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17780371010303497 | lossAlign: 0 +2025-09-21 12:42:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18637274205684662 | lossAlign: 0 +2025-09-21 12:42:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2255900353193283 | lossAlign: 0 +2025-09-21 12:42:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18937836587429047 | lossAlign: 0 +2025-09-21 12:42:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18187785148620605 | lossAlign: 0 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temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20206429064273834 | lossAlign: 0 +2025-09-21 12:42:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1666382998228073 | lossAlign: 0 +2025-09-21 12:42:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.175707146525383 | lossAlign: 0 +2025-09-21 12:43:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17387168109416962 | lossAlign: 0 +2025-09-21 12:43:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17548653483390808 | lossAlign: 0 +2025-09-21 12:43:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21854156255722046 | lossAlign: 0 +2025-09-21 12:43:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22173956036567688 | lossAlign: 0 +2025-09-21 12:43:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19115659594535828 | lossAlign: 0 +2025-09-21 12:43:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19663278758525848 | lossAlign: 0 +2025-09-21 12:43:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20478519797325134 | lossAlign: 0 +2025-09-21 12:43:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18665923178195953 | lossAlign: 0 +2025-09-21 12:43:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18083588778972626 | lossAlign: 0 +2025-09-21 12:43:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21736611425876617 | lossAlign: 0 +2025-09-21 12:43:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:43:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:43:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18812809884548187 | lossAlign: 0 +2025-09-21 12:43:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18997295200824738 | lossAlign: 0 +2025-09-21 12:43:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16069549322128296 | lossAlign: 0 +2025-09-21 12:43:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19439277052879333 | lossAlign: 0 +2025-09-21 12:43:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20599815249443054 | lossAlign: 0 +2025-09-21 12:43:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18720760941505432 | lossAlign: 0 +2025-09-21 12:43:33 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:43:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17635944485664368 | lossAlign: 0 +2025-09-21 12:43:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20000344514846802 | lossAlign: 0 +2025-09-21 12:43:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18200087547302246 | lossAlign: 0 +2025-09-21 12:43:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23942458629608154 | lossAlign: 0 +2025-09-21 12:43:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21087980270385742 | lossAlign: 0 +2025-09-21 12:43:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.196452796459198 | lossAlign: 0 +2025-09-21 12:43:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16931037604808807 | lossAlign: 0 +2025-09-21 12:43:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1709667444229126 | lossAlign: 0 +2025-09-21 12:43:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2079281061887741 | lossAlign: 0 +2025-09-21 12:43:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18174393475055695 | lossAlign: 0 +2025-09-21 12:43:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21514305472373962 | lossAlign: 0 +2025-09-21 12:43:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18139080703258514 | lossAlign: 0 +2025-09-21 12:43:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:43:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19104236364364624 | lossAlign: 0 +2025-09-21 12:43:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18456731736660004 | lossAlign: 0 +2025-09-21 12:44:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19424735009670258 | lossAlign: 0 +2025-09-21 12:44:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18115012347698212 | lossAlign: 0 +2025-09-21 12:44:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20213696360588074 | lossAlign: 0 +2025-09-21 12:44:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19781334698200226 | lossAlign: 0 +2025-09-21 12:44:10 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:44:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19678477942943573 | lossAlign: 0 +2025-09-21 12:44:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17350126802921295 | lossAlign: 0 +2025-09-21 12:44:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17591702938079834 | lossAlign: 0 +2025-09-21 12:44:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2162281572818756 | lossAlign: 0 +2025-09-21 12:44:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15666496753692627 | lossAlign: 0 +2025-09-21 12:44:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1829138845205307 | lossAlign: 0 +2025-09-21 12:44:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16762252151966095 | lossAlign: 0 +2025-09-21 12:44:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18952004611492157 | lossAlign: 0 +2025-09-21 12:44:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22007694840431213 | lossAlign: 0 +2025-09-21 12:44:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19309528172016144 | lossAlign: 0 +2025-09-21 12:44:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17294315993785858 | lossAlign: 0 +2025-09-21 12:44:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18748751282691956 | lossAlign: 0 +2025-09-21 12:44:35 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:44:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20422659814357758 | lossAlign: 0 +2025-09-21 12:44:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17940641939640045 | lossAlign: 0 +2025-09-21 12:44:39 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:44:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17836059629917145 | lossAlign: 0 +2025-09-21 12:44:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18710802495479584 | lossAlign: 0 +2025-09-21 12:44:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:44:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:44:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16957102715969086 | lossAlign: 0 +2025-09-21 12:44:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17509835958480835 | lossAlign: 0 +2025-09-21 12:44:47 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:44:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1904996633529663 | lossAlign: 0 +2025-09-21 12:44:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1951083540916443 | lossAlign: 0 +2025-09-21 12:44:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1861671805381775 | lossAlign: 0 +2025-09-21 12:44:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2032558172941208 | lossAlign: 0 +2025-09-21 12:44:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.179160475730896 | lossAlign: 0 +2025-09-21 12:44:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21042324602603912 | lossAlign: 0 +2025-09-21 12:45:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1747920662164688 | lossAlign: 0 +2025-09-21 12:45:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18978695571422577 | lossAlign: 0 +2025-09-21 12:45:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20143885910511017 | lossAlign: 0 +2025-09-21 12:45:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19414173066616058 | lossAlign: 0 +2025-09-21 12:45:08 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:45:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22045519948005676 | lossAlign: 0 +2025-09-21 12:45:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20554819703102112 | lossAlign: 0 +2025-09-21 12:45:12 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:45:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16756649315357208 | lossAlign: 0 +2025-09-21 12:45:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23981152474880219 | lossAlign: 0 +2025-09-21 12:45:16 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:45:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19059216976165771 | lossAlign: 0 +2025-09-21 12:45:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19806253910064697 | lossAlign: 0 +2025-09-21 12:45:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18923023343086243 | lossAlign: 0 +2025-09-21 12:45:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16600631177425385 | lossAlign: 0 +2025-09-21 12:45:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19023144245147705 | lossAlign: 0 +2025-09-21 12:45:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19887377321720123 | lossAlign: 0 +2025-09-21 12:45:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2208341509103775 | lossAlign: 0 +2025-09-21 12:45:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22014307975769043 | lossAlign: 0 +2025-09-21 12:45:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.214096799492836 | lossAlign: 0 +2025-09-21 12:45:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25750213861465454 | lossAlign: 0 +2025-09-21 12:45:36 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:45:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18814077973365784 | lossAlign: 0 +2025-09-21 12:45:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21105152368545532 | lossAlign: 0 +2025-09-21 12:45:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17592480778694153 | lossAlign: 0 +2025-09-21 12:45:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20583170652389526 | lossAlign: 0 +2025-09-21 12:45:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20434600114822388 | lossAlign: 0 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[] +2025-09-21 12:46:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1928805112838745 | lossAlign: 0 +2025-09-21 12:46:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1998901218175888 | lossAlign: 0 +2025-09-21 12:46:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22710081934928894 | lossAlign: 0 +2025-09-21 12:46:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20079056918621063 | lossAlign: 0 +2025-09-21 12:46:22 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:46:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18405930697917938 | lossAlign: 0 +2025-09-21 12:46:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21952064335346222 | lossAlign: 0 +2025-09-21 12:46:26 | INFO | LVLM-Med | Wrong this box: [] 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0 | alpha: 1.0 | decoder_output_loss: 0.1918017864227295 | lossAlign: 0 +2025-09-21 12:46:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17482410371303558 | lossAlign: 0 +2025-09-21 12:46:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17969419062137604 | lossAlign: 0 +2025-09-21 12:46:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17800520360469818 | lossAlign: 0 +2025-09-21 12:46:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19464638829231262 | lossAlign: 0 +2025-09-21 12:46:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18473964929580688 | lossAlign: 0 +2025-09-21 12:46:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:46:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19354897737503052 | lossAlign: 0 +2025-09-21 12:46:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1628410369157791 | lossAlign: 0 +2025-09-21 12:46:55 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:46:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16052603721618652 | lossAlign: 0 +2025-09-21 12:46:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18713217973709106 | lossAlign: 0 +2025-09-21 12:47:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17625413835048676 | lossAlign: 0 +2025-09-21 12:47:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19645822048187256 | lossAlign: 0 +2025-09-21 12:47:03 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:47:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16532108187675476 | lossAlign: 0 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0 | alpha: 1.0 | decoder_output_loss: 0.17481346428394318 | lossAlign: 0 +2025-09-21 12:47:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:47:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:47:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20092026889324188 | lossAlign: 0 +2025-09-21 12:47:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1805247962474823 | lossAlign: 0 +2025-09-21 12:47:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19233454763889313 | lossAlign: 0 +2025-09-21 12:47:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2097092568874359 | lossAlign: 0 +2025-09-21 12:47:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:47:28 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:47:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1899328976869583 | lossAlign: 0 +2025-09-21 12:47:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18038873374462128 | lossAlign: 0 +2025-09-21 12:47:31 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:47:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19234947860240936 | lossAlign: 0 +2025-09-21 12:47:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1877134144306183 | lossAlign: 0 +2025-09-21 12:47:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1791766881942749 | lossAlign: 0 +2025-09-21 12:47:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1767256110906601 | lossAlign: 0 +2025-09-21 12:47:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16346585750579834 | lossAlign: 0 +2025-09-21 12:47:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19854699075222015 | lossAlign: 0 +2025-09-21 12:47:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2245645374059677 | lossAlign: 0 +2025-09-21 12:47:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17187441885471344 | lossAlign: 0 +2025-09-21 12:47:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:47:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2105918973684311 | lossAlign: 0 +2025-09-21 12:47:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2112923562526703 | lossAlign: 0 +2025-09-21 12:47:52 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:47:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16947098076343536 | lossAlign: 0 +2025-09-21 12:47:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2168121635913849 | lossAlign: 0 +2025-09-21 12:47:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1986113339662552 | lossAlign: 0 +2025-09-21 12:47:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18008120357990265 | lossAlign: 0 +2025-09-21 12:48:00 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:48:00 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:48:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2388838678598404 | lossAlign: 0 +2025-09-21 12:48:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1966380774974823 | lossAlign: 0 +2025-09-21 12:48:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19994287192821503 | lossAlign: 0 +2025-09-21 12:48:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21178081631660461 | lossAlign: 0 +2025-09-21 12:48:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1690109670162201 | lossAlign: 0 +2025-09-21 12:48:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1970020979642868 | lossAlign: 0 +2025-09-21 12:48:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20107805728912354 | lossAlign: 0 +2025-09-21 12:48:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22236216068267822 | lossAlign: 0 +2025-09-21 12:48:17 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:48:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18311519920825958 | lossAlign: 0 +2025-09-21 12:48:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19173476099967957 | lossAlign: 0 +2025-09-21 12:48:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18591295182704926 | lossAlign: 0 +2025-09-21 12:48:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20159366726875305 | lossAlign: 0 +2025-09-21 12:48:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2029881775379181 | lossAlign: 0 +2025-09-21 12:48:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19087758660316467 | lossAlign: 0 +2025-09-21 12:48:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18390659987926483 | lossAlign: 0 +2025-09-21 12:48:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22038914263248444 | lossAlign: 0 +2025-09-21 12:48:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2191144824028015 | lossAlign: 0 +2025-09-21 12:48:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25435519218444824 | lossAlign: 0 +2025-09-21 12:48:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:48:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23262855410575867 | lossAlign: 0 +2025-09-21 12:48:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17821311950683594 | lossAlign: 0 +2025-09-21 12:48:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1780831664800644 | lossAlign: 0 +2025-09-21 12:48:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18166515231132507 | lossAlign: 0 +2025-09-21 12:48:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19178533554077148 | lossAlign: 0 +2025-09-21 12:48:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1924491822719574 | lossAlign: 0 +2025-09-21 12:48:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2097860723733902 | lossAlign: 0 +2025-09-21 12:48:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19778409600257874 | lossAlign: 0 +2025-09-21 12:48:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23432916402816772 | lossAlign: 0 +2025-09-21 12:48:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2527898848056793 | lossAlign: 0 +2025-09-21 12:48:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1870701164007187 | lossAlign: 0 +2025-09-21 12:48:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1738838404417038 | lossAlign: 0 +2025-09-21 12:49:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16460254788398743 | lossAlign: 0 +2025-09-21 12:49:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16959190368652344 | lossAlign: 0 +2025-09-21 12:49:06 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:06 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16847066581249237 | lossAlign: 0 +2025-09-21 12:49:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1936938315629959 | lossAlign: 0 +2025-09-21 12:49:10 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1992655098438263 | lossAlign: 0 +2025-09-21 12:49:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19291527569293976 | lossAlign: 0 +2025-09-21 12:49:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17304551601409912 | lossAlign: 0 +2025-09-21 12:49:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20565703511238098 | lossAlign: 0 +2025-09-21 12:49:18 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17358972132205963 | lossAlign: 0 +2025-09-21 12:49:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1663583219051361 | lossAlign: 0 +2025-09-21 12:49:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17849940061569214 | lossAlign: 0 +2025-09-21 12:49:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1667681187391281 | lossAlign: 0 +2025-09-21 12:49:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2159314751625061 | lossAlign: 0 +2025-09-21 12:49:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19501975178718567 | lossAlign: 0 +2025-09-21 12:49:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19431518018245697 | lossAlign: 0 +2025-09-21 12:49:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17920947074890137 | lossAlign: 0 +2025-09-21 12:49:35 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19591519236564636 | lossAlign: 0 +2025-09-21 12:49:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19980034232139587 | lossAlign: 0 +2025-09-21 12:49:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20310011506080627 | lossAlign: 0 +2025-09-21 12:49:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19295841455459595 | lossAlign: 0 +2025-09-21 12:49:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:49:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1866147518157959 | lossAlign: 0 +2025-09-21 12:49:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18093989789485931 | lossAlign: 0 +2025-09-21 12:49:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18415190279483795 | lossAlign: 0 +2025-09-21 12:49:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1895626038312912 | lossAlign: 0 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lossAlign: 0 +2025-09-21 12:50:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1912422776222229 | lossAlign: 0 +2025-09-21 12:50:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1781700700521469 | lossAlign: 0 +2025-09-21 12:50:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19284038245677948 | lossAlign: 0 +2025-09-21 12:50:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25963035225868225 | lossAlign: 0 +2025-09-21 12:50:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17887896299362183 | lossAlign: 0 +2025-09-21 12:50:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17940890789031982 | lossAlign: 0 +2025-09-21 12:50:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17112314701080322 | lossAlign: 0 +2025-09-21 12:50:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:50:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22197183966636658 | lossAlign: 0 +2025-09-21 12:50:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2032124251127243 | lossAlign: 0 +2025-09-21 12:50:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1773359626531601 | lossAlign: 0 +2025-09-21 12:50:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20024651288986206 | lossAlign: 0 +2025-09-21 12:50:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1935589760541916 | lossAlign: 0 +2025-09-21 12:50:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18525345623493195 | lossAlign: 0 +2025-09-21 12:50:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21478888392448425 | lossAlign: 0 +2025-09-21 12:50:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2364846020936966 | lossAlign: 0 +2025-09-21 12:50:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1966857612133026 | lossAlign: 0 +2025-09-21 12:50:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18685846030712128 | lossAlign: 0 +2025-09-21 12:50:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1894385665655136 | lossAlign: 0 +2025-09-21 12:50:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15094415843486786 | lossAlign: 0 +2025-09-21 12:50:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:50:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1871260106563568 | lossAlign: 0 +2025-09-21 12:50:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21833796799182892 | lossAlign: 0 +2025-09-21 12:50:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17006815969944 | lossAlign: 0 +2025-09-21 12:50:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19014564156532288 | lossAlign: 0 +2025-09-21 12:50:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20088224112987518 | lossAlign: 0 +2025-09-21 12:50:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.3551097512245178 | lossAlign: 0 +2025-09-21 12:50:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23486842215061188 | lossAlign: 0 +2025-09-21 12:50:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18468330800533295 | lossAlign: 0 +2025-09-21 12:51:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15581101179122925 | lossAlign: 0 +2025-09-21 12:51:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17298084497451782 | lossAlign: 0 +2025-09-21 12:51:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1901046335697174 | lossAlign: 0 +2025-09-21 12:51:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18853995203971863 | lossAlign: 0 +2025-09-21 12:51:08 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:51:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19067269563674927 | lossAlign: 0 +2025-09-21 12:51:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18582086265087128 | lossAlign: 0 +2025-09-21 12:51:13 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:51:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1877412497997284 | lossAlign: 0 +2025-09-21 12:51:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2062859982252121 | lossAlign: 0 +2025-09-21 12:51:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1822088360786438 | lossAlign: 0 +2025-09-21 12:51:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18286940455436707 | lossAlign: 0 +2025-09-21 12:51:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17100971937179565 | lossAlign: 0 +2025-09-21 12:51:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16355343163013458 | lossAlign: 0 +2025-09-21 12:51:25 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:51:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17408937215805054 | lossAlign: 0 +2025-09-21 12:51:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20402006804943085 | lossAlign: 0 +2025-09-21 12:51:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19145779311656952 | lossAlign: 0 +2025-09-21 12:51:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18904782831668854 | lossAlign: 0 +2025-09-21 12:51:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18009112775325775 | lossAlign: 0 +2025-09-21 12:51:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18579639494419098 | lossAlign: 0 +2025-09-21 12:51:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:51:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18014872074127197 | lossAlign: 0 +2025-09-21 12:51:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17760388553142548 | lossAlign: 0 +2025-09-21 12:51:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:51:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16722427308559418 | lossAlign: 0 +2025-09-21 12:51:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17715850472450256 | lossAlign: 0 +2025-09-21 12:51:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2328980267047882 | lossAlign: 0 +2025-09-21 12:51:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1946987807750702 | lossAlign: 0 +2025-09-21 12:51:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:51:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17324243485927582 | lossAlign: 0 +2025-09-21 12:51:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1741710752248764 | lossAlign: 0 +2025-09-21 12:51:54 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:51:54 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:51:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21590955555438995 | lossAlign: 0 +2025-09-21 12:51:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2137146145105362 | lossAlign: 0 +2025-09-21 12:51:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19726210832595825 | lossAlign: 0 +2025-09-21 12:51:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2260850965976715 | lossAlign: 0 +2025-09-21 12:52:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17913897335529327 | lossAlign: 0 +2025-09-21 12:52:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20855964720249176 | lossAlign: 0 +2025-09-21 12:52:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1914481222629547 | lossAlign: 0 +2025-09-21 12:52:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14967328310012817 | lossAlign: 0 +2025-09-21 12:52:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20899035036563873 | lossAlign: 0 +2025-09-21 12:52:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1650785654783249 | lossAlign: 0 +2025-09-21 12:52:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18307189643383026 | lossAlign: 0 +2025-09-21 12:52:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16759848594665527 | lossAlign: 0 +2025-09-21 12:52:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18427732586860657 | lossAlign: 0 +2025-09-21 12:52:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1759377419948578 | lossAlign: 0 +2025-09-21 12:52:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1963607668876648 | lossAlign: 0 +2025-09-21 12:52:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1963447630405426 | lossAlign: 0 +2025-09-21 12:52:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:52:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:52:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1736677885055542 | lossAlign: 0 +2025-09-21 12:52:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17120413482189178 | lossAlign: 0 +2025-09-21 12:52:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1933845579624176 | lossAlign: 0 +2025-09-21 12:52:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2090877741575241 | lossAlign: 0 +2025-09-21 12:52:36 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:52:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1580156683921814 | lossAlign: 0 +2025-09-21 12:52:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1755092889070511 | lossAlign: 0 +2025-09-21 12:52:40 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:52:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18540409207344055 | lossAlign: 0 +2025-09-21 12:52:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1764182299375534 | lossAlign: 0 +2025-09-21 12:52:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18846797943115234 | lossAlign: 0 +2025-09-21 12:52:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1776697039604187 | lossAlign: 0 +2025-09-21 12:52:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:52:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17972053587436676 | lossAlign: 0 +2025-09-21 12:52:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17798642814159393 | lossAlign: 0 +2025-09-21 12:52:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17320653796195984 | lossAlign: 0 +2025-09-21 12:52:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17849893867969513 | lossAlign: 0 +2025-09-21 12:52:56 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:52:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2037193924188614 | lossAlign: 0 +2025-09-21 12:52:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.152885302901268 | lossAlign: 0 +2025-09-21 12:53:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17239107191562653 | lossAlign: 0 +2025-09-21 12:53:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18843792378902435 | lossAlign: 0 +2025-09-21 12:53:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25490903854370117 | lossAlign: 0 +2025-09-21 12:53:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18733453750610352 | lossAlign: 0 +2025-09-21 12:53:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23003889620304108 | lossAlign: 0 +2025-09-21 12:53:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23046496510505676 | lossAlign: 0 +2025-09-21 12:53:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19776968657970428 | lossAlign: 0 +2025-09-21 12:53:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18607880175113678 | lossAlign: 0 +2025-09-21 12:53:17 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:53:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17421860992908478 | lossAlign: 0 +2025-09-21 12:53:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2121250033378601 | lossAlign: 0 +2025-09-21 12:53:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1588193029165268 | lossAlign: 0 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lossAlign: 0 +2025-09-21 12:53:38 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:53:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1911810338497162 | lossAlign: 0 +2025-09-21 12:53:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17232553660869598 | lossAlign: 0 +2025-09-21 12:53:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:53:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:53:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1631094366312027 | lossAlign: 0 +2025-09-21 12:53:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1818258911371231 | lossAlign: 0 +2025-09-21 12:53:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17133033275604248 | lossAlign: 0 +2025-09-21 12:53:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21413923799991608 | lossAlign: 0 +2025-09-21 12:53:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18148399889469147 | lossAlign: 0 +2025-09-21 12:53:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24096503853797913 | lossAlign: 0 +2025-09-21 12:53:54 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:53:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18910647928714752 | lossAlign: 0 +2025-09-21 12:53:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17050597071647644 | lossAlign: 0 +2025-09-21 12:53:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:53:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17632324993610382 | lossAlign: 0 +2025-09-21 12:53:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.24434609711170197 | lossAlign: 0 +2025-09-21 12:54:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1792873740196228 | lossAlign: 0 +2025-09-21 12:54:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.28634515404701233 | lossAlign: 0 +2025-09-21 12:54:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16892902553081512 | lossAlign: 0 +2025-09-21 12:54:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1942562609910965 | lossAlign: 0 +2025-09-21 12:54:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19261299073696136 | lossAlign: 0 +2025-09-21 12:54:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2005164921283722 | lossAlign: 0 +2025-09-21 12:54:15 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:54:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18104606866836548 | lossAlign: 0 +2025-09-21 12:54:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19332797825336456 | lossAlign: 0 +2025-09-21 12:54:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19014817476272583 | lossAlign: 0 +2025-09-21 12:54:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19169661402702332 | lossAlign: 0 +2025-09-21 12:54:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.186172217130661 | lossAlign: 0 +2025-09-21 12:54:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22197967767715454 | lossAlign: 0 +2025-09-21 12:54:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21062082052230835 | lossAlign: 0 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| alpha: 1.0 | decoder_output_loss: 0.19483782351016998 | lossAlign: 0 +2025-09-21 12:54:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20742948353290558 | lossAlign: 0 +2025-09-21 12:54:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1829482614994049 | lossAlign: 0 +2025-09-21 12:54:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19576376676559448 | lossAlign: 0 +2025-09-21 12:54:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20253147184848785 | lossAlign: 0 +2025-09-21 12:54:52 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:54:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18677271902561188 | lossAlign: 0 +2025-09-21 12:54:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17497970163822174 | lossAlign: 0 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decoder_output_loss: 0.16518433392047882 | lossAlign: 0 +2025-09-21 12:55:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16377460956573486 | lossAlign: 0 +2025-09-21 12:55:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17459465563297272 | lossAlign: 0 +2025-09-21 12:55:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17041930556297302 | lossAlign: 0 +2025-09-21 12:55:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17521026730537415 | lossAlign: 0 +2025-09-21 12:55:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.167746901512146 | lossAlign: 0 +2025-09-21 12:55:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.157587468624115 | lossAlign: 0 +2025-09-21 12:55:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1902807503938675 | lossAlign: 0 +2025-09-21 12:55:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18281587958335876 | lossAlign: 0 +2025-09-21 12:55:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20951545238494873 | lossAlign: 0 +2025-09-21 12:55:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17766959965229034 | lossAlign: 0 +2025-09-21 12:55:29 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:55:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1648334264755249 | lossAlign: 0 +2025-09-21 12:55:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1787596195936203 | lossAlign: 0 +2025-09-21 12:55:34 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:55:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16333132982254028 | lossAlign: 0 +2025-09-21 12:55:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1901690810918808 | lossAlign: 0 +2025-09-21 12:55:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22511883080005646 | lossAlign: 0 +2025-09-21 12:55:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18306758999824524 | lossAlign: 0 +2025-09-21 12:55:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1788858026266098 | lossAlign: 0 +2025-09-21 12:55:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15249881148338318 | lossAlign: 0 +2025-09-21 12:55:46 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:55:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14907577633857727 | lossAlign: 0 +2025-09-21 12:55:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20574675500392914 | lossAlign: 0 +2025-09-21 12:55:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19302035868167877 | lossAlign: 0 +2025-09-21 12:55:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17148424685001373 | lossAlign: 0 +2025-09-21 12:55:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2042967528104782 | lossAlign: 0 +2025-09-21 12:55:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2093760073184967 | lossAlign: 0 +2025-09-21 12:56:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18490511178970337 | lossAlign: 0 +2025-09-21 12:56:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18352140486240387 | lossAlign: 0 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12:56:16 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:56:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19103538990020752 | lossAlign: 0 +2025-09-21 12:56:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17853088676929474 | lossAlign: 0 +2025-09-21 12:56:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1716737598180771 | lossAlign: 0 +2025-09-21 12:56:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20296476781368256 | lossAlign: 0 +2025-09-21 12:56:24 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:56:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17254169285297394 | lossAlign: 0 +2025-09-21 12:56:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18263185024261475 | lossAlign: 0 +2025-09-21 12:56:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17250312864780426 | lossAlign: 0 +2025-09-21 12:56:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17187713086605072 | lossAlign: 0 +2025-09-21 12:56:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1606859713792801 | lossAlign: 0 +2025-09-21 12:56:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.180991992354393 | lossAlign: 0 +2025-09-21 12:56:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1982780396938324 | lossAlign: 0 +2025-09-21 12:56:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19706906378269196 | lossAlign: 0 +2025-09-21 12:56:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1787600815296173 | lossAlign: 0 +2025-09-21 12:56:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18299514055252075 | lossAlign: 0 +2025-09-21 12:56:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1837441772222519 | lossAlign: 0 +2025-09-21 12:56:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16441726684570312 | lossAlign: 0 +2025-09-21 12:56:49 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:56:49 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:56:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.192339226603508 | lossAlign: 0 +2025-09-21 12:56:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1714521050453186 | lossAlign: 0 +2025-09-21 12:56:53 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:56:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2097746580839157 | lossAlign: 0 +2025-09-21 12:56:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22645065188407898 | lossAlign: 0 +2025-09-21 12:56:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17886857688426971 | lossAlign: 0 +2025-09-21 12:56:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2114570438861847 | lossAlign: 0 +2025-09-21 12:57:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1782522201538086 | lossAlign: 0 +2025-09-21 12:57:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20920558273792267 | lossAlign: 0 +2025-09-21 12:57:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18437084555625916 | lossAlign: 0 +2025-09-21 12:57:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18872764706611633 | lossAlign: 0 +2025-09-21 12:57:10 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:57:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18238084018230438 | lossAlign: 0 +2025-09-21 12:57:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16599519550800323 | lossAlign: 0 +2025-09-21 12:57:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18219846487045288 | lossAlign: 0 +2025-09-21 12:57:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1605369597673416 | lossAlign: 0 +2025-09-21 12:57:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16989536583423615 | lossAlign: 0 +2025-09-21 12:57:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18609346449375153 | lossAlign: 0 +2025-09-21 12:57:22 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:57:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17639997601509094 | lossAlign: 0 +2025-09-21 12:57:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16345873475074768 | lossAlign: 0 +2025-09-21 12:57:26 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:57:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15128032863140106 | lossAlign: 0 +2025-09-21 12:57:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17686770856380463 | lossAlign: 0 +2025-09-21 12:57:30 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:57:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15687011182308197 | lossAlign: 0 +2025-09-21 12:57:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18143290281295776 | lossAlign: 0 +2025-09-21 12:57:34 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:57:35 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:57:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15248003602027893 | lossAlign: 0 +2025-09-21 12:57:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17515601217746735 | lossAlign: 0 +2025-09-21 12:57:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20036451518535614 | lossAlign: 0 +2025-09-21 12:57:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15551677346229553 | lossAlign: 0 +2025-09-21 12:57:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18922032415866852 | lossAlign: 0 +2025-09-21 12:57:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15154020488262177 | lossAlign: 0 +2025-09-21 12:57:47 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:57:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1607043445110321 | lossAlign: 0 +2025-09-21 12:57:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1621084362268448 | lossAlign: 0 +2025-09-21 12:57:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17512913048267365 | lossAlign: 0 +2025-09-21 12:57:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19573551416397095 | lossAlign: 0 +2025-09-21 12:57:55 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:57:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17177027463912964 | lossAlign: 0 +2025-09-21 12:57:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16497577726840973 | lossAlign: 0 +2025-09-21 12:58:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15224026143550873 | lossAlign: 0 +2025-09-21 12:58:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15019837021827698 | lossAlign: 0 +2025-09-21 12:58:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2181878387928009 | lossAlign: 0 +2025-09-21 12:58:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16233046352863312 | lossAlign: 0 +2025-09-21 12:58:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17151851952075958 | lossAlign: 0 +2025-09-21 12:58:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16496722400188446 | lossAlign: 0 +2025-09-21 12:58:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.157081738114357 | lossAlign: 0 +2025-09-21 12:58:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16606123745441437 | lossAlign: 0 +2025-09-21 12:58:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1563151627779007 | lossAlign: 0 +2025-09-21 12:58:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15123197436332703 | lossAlign: 0 +2025-09-21 12:58:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1895039826631546 | lossAlign: 0 +2025-09-21 12:58:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16485679149627686 | lossAlign: 0 +2025-09-21 12:58:24 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:58:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1534145623445511 | lossAlign: 0 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| alpha: 1.0 | decoder_output_loss: 0.2143806666135788 | lossAlign: 0 +2025-09-21 12:58:40 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:58:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:58:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1776442974805832 | lossAlign: 0 +2025-09-21 12:58:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1757831573486328 | lossAlign: 0 +2025-09-21 12:58:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1740225851535797 | lossAlign: 0 +2025-09-21 12:58:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16666962206363678 | lossAlign: 0 +2025-09-21 12:58:49 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:58:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1577228307723999 | lossAlign: 0 +2025-09-21 12:58:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15820930898189545 | lossAlign: 0 +2025-09-21 12:58:53 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:58:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15268418192863464 | lossAlign: 0 +2025-09-21 12:58:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20147714018821716 | lossAlign: 0 +2025-09-21 12:58:57 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:58:57 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:58:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1620940864086151 | lossAlign: 0 +2025-09-21 12:58:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16239669919013977 | lossAlign: 0 +2025-09-21 12:59:01 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:59:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15129193663597107 | lossAlign: 0 +2025-09-21 12:59:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13677386939525604 | lossAlign: 0 +2025-09-21 12:59:05 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:59:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17120113968849182 | lossAlign: 0 +2025-09-21 12:59:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.154906764626503 | lossAlign: 0 +2025-09-21 12:59:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16908995807170868 | lossAlign: 0 +2025-09-21 12:59:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16236403584480286 | lossAlign: 0 +2025-09-21 12:59:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20166848599910736 | lossAlign: 0 +2025-09-21 12:59:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15134744346141815 | lossAlign: 0 +2025-09-21 12:59:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1542288064956665 | lossAlign: 0 +2025-09-21 12:59:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14830081164836884 | lossAlign: 0 +2025-09-21 12:59:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1616223305463791 | lossAlign: 0 +2025-09-21 12:59:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16814596951007843 | lossAlign: 0 +2025-09-21 12:59:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17503070831298828 | lossAlign: 0 +2025-09-21 12:59:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15062926709651947 | lossAlign: 0 +2025-09-21 12:59:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16517187654972076 | lossAlign: 0 +2025-09-21 12:59:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1696232557296753 | lossAlign: 0 +2025-09-21 12:59:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16830572485923767 | lossAlign: 0 +2025-09-21 12:59:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16936811804771423 | lossAlign: 0 +2025-09-21 12:59:38 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:59:38 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:59:38 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 12:59:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16419477760791779 | lossAlign: 0 +2025-09-21 12:59:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1614551693201065 | lossAlign: 0 +2025-09-21 12:59:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17670024931430817 | lossAlign: 0 +2025-09-21 12:59:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18079371750354767 | lossAlign: 0 +2025-09-21 12:59:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1322745829820633 | lossAlign: 0 +2025-09-21 12:59:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16663213074207306 | lossAlign: 0 +2025-09-21 12:59:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15912246704101562 | lossAlign: 0 +2025-09-21 12:59:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2041320502758026 | lossAlign: 0 +2025-09-21 12:59:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16722649335861206 | lossAlign: 0 +2025-09-21 12:59:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1609129011631012 | lossAlign: 0 +2025-09-21 12:59:59 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:00:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19652213156223297 | lossAlign: 0 +2025-09-21 13:00:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15707673132419586 | lossAlign: 0 +2025-09-21 13:00:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1696663498878479 | lossAlign: 0 +2025-09-21 13:00:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16058848798274994 | lossAlign: 0 +2025-09-21 13:00:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16679538786411285 | lossAlign: 0 +2025-09-21 13:00:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1527477353811264 | lossAlign: 0 +2025-09-21 13:00:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16278663277626038 | lossAlign: 0 +2025-09-21 13:00:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22495877742767334 | lossAlign: 0 +2025-09-21 13:00:15 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:00:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15440045297145844 | lossAlign: 0 +2025-09-21 13:00:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14809051156044006 | lossAlign: 0 +2025-09-21 13:00:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19352297484874725 | lossAlign: 0 +2025-09-21 13:00:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1478434056043625 | lossAlign: 0 +2025-09-21 13:00:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16574177145957947 | lossAlign: 0 +2025-09-21 13:00:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17319004237651825 | lossAlign: 0 +2025-09-21 13:00:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18881718814373016 | lossAlign: 0 +2025-09-21 13:00:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17014195024967194 | lossAlign: 0 +2025-09-21 13:00:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1646944284439087 | lossAlign: 0 +2025-09-21 13:00:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17250756919384003 | lossAlign: 0 +2025-09-21 13:00:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16851304471492767 | lossAlign: 0 +2025-09-21 13:00:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17770709097385406 | lossAlign: 0 +2025-09-21 13:00:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17716051638126373 | lossAlign: 0 +2025-09-21 13:00:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21988607943058014 | lossAlign: 0 +2025-09-21 13:00:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15890982747077942 | lossAlign: 0 +2025-09-21 13:00:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16091199219226837 | lossAlign: 0 +2025-09-21 13:00:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:00:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:00:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14807313680648804 | lossAlign: 0 +2025-09-21 13:00:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19887593388557434 | lossAlign: 0 +2025-09-21 13:00:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1615508794784546 | lossAlign: 0 +2025-09-21 13:00:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16544562578201294 | lossAlign: 0 +2025-09-21 13:00:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1549323946237564 | lossAlign: 0 +2025-09-21 13:00:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15860840678215027 | lossAlign: 0 +2025-09-21 13:01:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17081604897975922 | lossAlign: 0 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0 | alpha: 1.0 | decoder_output_loss: 0.1406852900981903 | lossAlign: 0 +2025-09-21 13:01:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17750507593154907 | lossAlign: 0 +2025-09-21 13:01:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1606445461511612 | lossAlign: 0 +2025-09-21 13:01:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15422262251377106 | lossAlign: 0 +2025-09-21 13:01:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1705305576324463 | lossAlign: 0 +2025-09-21 13:01:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20627549290657043 | lossAlign: 0 +2025-09-21 13:01:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16552452743053436 | lossAlign: 0 +2025-09-21 13:01:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1748640090227127 | lossAlign: 0 +2025-09-21 13:01:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15284115076065063 | lossAlign: 0 +2025-09-21 13:01:33 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:01:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19214044511318207 | lossAlign: 0 +2025-09-21 13:01:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18990732729434967 | lossAlign: 0 +2025-09-21 13:01:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:01:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:01:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19197185337543488 | lossAlign: 0 +2025-09-21 13:01:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1717897206544876 | lossAlign: 0 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0 | alpha: 1.0 | decoder_output_loss: 0.16861432790756226 | lossAlign: 0 +2025-09-21 13:01:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15557754039764404 | lossAlign: 0 +2025-09-21 13:01:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15136714279651642 | lossAlign: 0 +2025-09-21 13:01:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15153615176677704 | lossAlign: 0 +2025-09-21 13:02:01 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:02:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15104109048843384 | lossAlign: 0 +2025-09-21 13:02:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14696195721626282 | lossAlign: 0 +2025-09-21 13:02:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15949496626853943 | lossAlign: 0 +2025-09-21 13:02:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15058031678199768 | lossAlign: 0 +2025-09-21 13:02:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15245728194713593 | lossAlign: 0 +2025-09-21 13:02:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16310350596904755 | lossAlign: 0 +2025-09-21 13:02:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17719969153404236 | lossAlign: 0 +2025-09-21 13:02:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1626376360654831 | lossAlign: 0 +2025-09-21 13:02:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18575671315193176 | lossAlign: 0 +2025-09-21 13:02:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16946841776371002 | lossAlign: 0 +2025-09-21 13:02:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15802133083343506 | lossAlign: 0 +2025-09-21 13:02:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16153346002101898 | lossAlign: 0 +2025-09-21 13:02:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16899612545967102 | lossAlign: 0 +2025-09-21 13:02:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16211090981960297 | lossAlign: 0 +2025-09-21 13:02:31 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:02:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1605527698993683 | lossAlign: 0 +2025-09-21 13:02:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22795619070529938 | lossAlign: 0 +2025-09-21 13:02:35 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:02:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.174428790807724 | lossAlign: 0 +2025-09-21 13:02:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15733543038368225 | lossAlign: 0 +2025-09-21 13:02:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17208042740821838 | lossAlign: 0 +2025-09-21 13:02:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16916343569755554 | lossAlign: 0 +2025-09-21 13:02:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15958315134048462 | lossAlign: 0 +2025-09-21 13:02:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17072953283786774 | lossAlign: 0 +2025-09-21 13:02:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16478075087070465 | lossAlign: 0 +2025-09-21 13:02:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1761474609375 | lossAlign: 0 +2025-09-21 13:02:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14761100709438324 | lossAlign: 0 +2025-09-21 13:02:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1549869328737259 | lossAlign: 0 +2025-09-21 13:02:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15883497893810272 | lossAlign: 0 +2025-09-21 13:02:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1587860882282257 | lossAlign: 0 +2025-09-21 13:03:00 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:03:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15978243947029114 | lossAlign: 0 +2025-09-21 13:03:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16865497827529907 | lossAlign: 0 +2025-09-21 13:03:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17134906351566315 | lossAlign: 0 +2025-09-21 13:03:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14009737968444824 | lossAlign: 0 +2025-09-21 13:03:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17701536417007446 | lossAlign: 0 +2025-09-21 13:03:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16726236045360565 | lossAlign: 0 +2025-09-21 13:03:13 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:03:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16294333338737488 | lossAlign: 0 +2025-09-21 13:03:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17449434101581573 | lossAlign: 0 +2025-09-21 13:03:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17292256653308868 | lossAlign: 0 +2025-09-21 13:03:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15377146005630493 | lossAlign: 0 +2025-09-21 13:03:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16834168136119843 | lossAlign: 0 +2025-09-21 13:03:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1640556901693344 | lossAlign: 0 +2025-09-21 13:03:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13929347693920135 | lossAlign: 0 +2025-09-21 13:03:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1533193439245224 | lossAlign: 0 +2025-09-21 13:03:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1702355295419693 | lossAlign: 0 +2025-09-21 13:03:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15957573056221008 | lossAlign: 0 +2025-09-21 13:03:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18456627428531647 | lossAlign: 0 +2025-09-21 13:03:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1615167260169983 | lossAlign: 0 +2025-09-21 13:03:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17387531697750092 | lossAlign: 0 +2025-09-21 13:03:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15539030730724335 | lossAlign: 0 +2025-09-21 13:03:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:03:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16244055330753326 | lossAlign: 0 +2025-09-21 13:03:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15758202970027924 | lossAlign: 0 +2025-09-21 13:03:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16252243518829346 | lossAlign: 0 +2025-09-21 13:03:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15459534525871277 | lossAlign: 0 +2025-09-21 13:03:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1941891610622406 | lossAlign: 0 +2025-09-21 13:03:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.23891688883304596 | lossAlign: 0 +2025-09-21 13:03:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14948400855064392 | lossAlign: 0 +2025-09-21 13:03:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15481126308441162 | lossAlign: 0 +2025-09-21 13:03:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:03:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:03:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:03:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1256619095802307 | lossAlign: 0 +2025-09-21 13:03:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16596147418022156 | lossAlign: 0 +2025-09-21 13:04:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15873731672763824 | lossAlign: 0 +2025-09-21 13:04:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1949387639760971 | lossAlign: 0 +2025-09-21 13:04:07 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:04:07 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:04:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15118137001991272 | lossAlign: 0 +2025-09-21 13:04:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1797185242176056 | lossAlign: 0 +2025-09-21 13:04:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20818766951560974 | lossAlign: 0 +2025-09-21 13:04:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16122403740882874 | lossAlign: 0 +2025-09-21 13:04:15 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:04:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18788225948810577 | lossAlign: 0 +2025-09-21 13:04:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1863635927438736 | lossAlign: 0 +2025-09-21 13:04:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14438945055007935 | lossAlign: 0 +2025-09-21 13:04:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1632193773984909 | lossAlign: 0 +2025-09-21 13:04:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15982142090797424 | lossAlign: 0 +2025-09-21 13:04:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1620967537164688 | lossAlign: 0 +2025-09-21 13:04:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:04:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1640133559703827 | lossAlign: 0 +2025-09-21 13:04:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16414432227611542 | lossAlign: 0 +2025-09-21 13:04:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16629907488822937 | lossAlign: 0 +2025-09-21 13:04:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1773720681667328 | lossAlign: 0 +2025-09-21 13:04:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15438784658908844 | lossAlign: 0 +2025-09-21 13:04:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15029439330101013 | lossAlign: 0 +2025-09-21 13:04:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16016323864459991 | lossAlign: 0 +2025-09-21 13:04:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1552119255065918 | lossAlign: 0 +2025-09-21 13:04:44 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:04:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16753949224948883 | lossAlign: 0 +2025-09-21 13:04:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15335382521152496 | lossAlign: 0 +2025-09-21 13:04:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:04:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16399306058883667 | lossAlign: 0 +2025-09-21 13:04:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19174526631832123 | lossAlign: 0 +2025-09-21 13:04:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14940200746059418 | lossAlign: 0 +2025-09-21 13:04:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16122418642044067 | lossAlign: 0 +2025-09-21 13:04:56 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:04:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1981251984834671 | lossAlign: 0 +2025-09-21 13:04:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1559239774942398 | lossAlign: 0 +2025-09-21 13:05:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15880656242370605 | lossAlign: 0 +2025-09-21 13:05:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15970978140830994 | lossAlign: 0 +2025-09-21 13:05:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15811622142791748 | lossAlign: 0 +2025-09-21 13:05:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1907283514738083 | lossAlign: 0 +2025-09-21 13:05:09 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:05:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15121245384216309 | lossAlign: 0 +2025-09-21 13:05:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1719444841146469 | lossAlign: 0 +2025-09-21 13:05:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17446956038475037 | lossAlign: 0 +2025-09-21 13:05:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15330584347248077 | lossAlign: 0 +2025-09-21 13:05:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1623247265815735 | lossAlign: 0 +2025-09-21 13:05:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1498350203037262 | lossAlign: 0 +2025-09-21 13:05:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:05:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1713366061449051 | lossAlign: 0 +2025-09-21 13:05:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1533663421869278 | lossAlign: 0 +2025-09-21 13:05:25 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:05:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16571083664894104 | lossAlign: 0 +2025-09-21 13:05:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15699438750743866 | lossAlign: 0 +2025-09-21 13:05:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15188784897327423 | lossAlign: 0 +2025-09-21 13:05:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17685188353061676 | lossAlign: 0 +2025-09-21 13:05:34 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:05:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18381917476654053 | lossAlign: 0 +2025-09-21 13:05:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15234839916229248 | lossAlign: 0 +2025-09-21 13:05:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1602029949426651 | lossAlign: 0 +2025-09-21 13:05:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15241427719593048 | lossAlign: 0 +2025-09-21 13:05:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:05:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16539597511291504 | lossAlign: 0 +2025-09-21 13:05:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16421446204185486 | lossAlign: 0 +2025-09-21 13:05:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17541302740573883 | lossAlign: 0 +2025-09-21 13:05:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19296766817569733 | lossAlign: 0 +2025-09-21 13:05:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:05:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14887961745262146 | lossAlign: 0 +2025-09-21 13:05:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13595041632652283 | lossAlign: 0 +2025-09-21 13:05:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15216879546642303 | lossAlign: 0 +2025-09-21 13:05:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16181053221225739 | lossAlign: 0 +2025-09-21 13:05:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1801527440547943 | lossAlign: 0 +2025-09-21 13:05:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1609850823879242 | lossAlign: 0 +2025-09-21 13:06:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:06:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:06:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17421318590641022 | lossAlign: 0 +2025-09-21 13:06:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1500181406736374 | lossAlign: 0 +2025-09-21 13:06:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14334051311016083 | lossAlign: 0 +2025-09-21 13:06:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17065811157226562 | lossAlign: 0 +2025-09-21 13:06:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15416686236858368 | lossAlign: 0 +2025-09-21 13:06:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14108578860759735 | lossAlign: 0 +2025-09-21 13:06:15 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:06:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.168113574385643 | lossAlign: 0 +2025-09-21 13:06:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1403324156999588 | lossAlign: 0 +2025-09-21 13:06:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:06:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1644754856824875 | lossAlign: 0 +2025-09-21 13:06:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1491570621728897 | lossAlign: 0 +2025-09-21 13:06:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1466943621635437 | lossAlign: 0 +2025-09-21 13:06:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1801609843969345 | lossAlign: 0 +2025-09-21 13:06:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16909384727478027 | lossAlign: 0 +2025-09-21 13:06:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14053864777088165 | lossAlign: 0 +2025-09-21 13:06:31 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:06:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14863428473472595 | lossAlign: 0 +2025-09-21 13:06:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18942105770111084 | lossAlign: 0 +2025-09-21 13:06:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1766968071460724 | lossAlign: 0 +2025-09-21 13:06:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1750641167163849 | lossAlign: 0 +2025-09-21 13:06:39 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:06:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18162629008293152 | lossAlign: 0 +2025-09-21 13:06:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1604832410812378 | lossAlign: 0 +2025-09-21 13:06:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16162557899951935 | lossAlign: 0 +2025-09-21 13:06:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17304208874702454 | lossAlign: 0 +2025-09-21 13:06:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:06:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1609524041414261 | lossAlign: 0 +2025-09-21 13:06:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16319365799427032 | lossAlign: 0 +2025-09-21 13:06:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16056278347969055 | lossAlign: 0 +2025-09-21 13:06:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16372689604759216 | lossAlign: 0 +2025-09-21 13:06:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15341100096702576 | lossAlign: 0 +2025-09-21 13:06:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1608409434556961 | lossAlign: 0 +2025-09-21 13:07:00 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:07:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20658662915229797 | lossAlign: 0 +2025-09-21 13:07:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15523554384708405 | lossAlign: 0 +2025-09-21 13:07:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.161099374294281 | lossAlign: 0 +2025-09-21 13:07:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15857645869255066 | lossAlign: 0 +2025-09-21 13:07:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14277201890945435 | lossAlign: 0 +2025-09-21 13:07:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16899487376213074 | lossAlign: 0 +2025-09-21 13:07:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15831822156906128 | lossAlign: 0 +2025-09-21 13:07:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.158364936709404 | lossAlign: 0 +2025-09-21 13:07:16 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:07:16 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:07:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1525721698999405 | lossAlign: 0 +2025-09-21 13:07:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19799791276454926 | lossAlign: 0 +2025-09-21 13:07:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.153578981757164 | lossAlign: 0 +2025-09-21 13:07:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16498903930187225 | lossAlign: 0 +2025-09-21 13:07:24 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:07:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16048435866832733 | lossAlign: 0 +2025-09-21 13:07:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.22351385653018951 | lossAlign: 0 +2025-09-21 13:07:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15448138117790222 | lossAlign: 0 +2025-09-21 13:07:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17917059361934662 | lossAlign: 0 +2025-09-21 13:07:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14685194194316864 | lossAlign: 0 +2025-09-21 13:07:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16474376618862152 | lossAlign: 0 +2025-09-21 13:07:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15040506422519684 | lossAlign: 0 +2025-09-21 13:07:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16577355563640594 | lossAlign: 0 +2025-09-21 13:07:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14739243686199188 | lossAlign: 0 +2025-09-21 13:07:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1563933938741684 | lossAlign: 0 +2025-09-21 13:07:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17185534536838531 | lossAlign: 0 +2025-09-21 13:07:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21804898977279663 | lossAlign: 0 +2025-09-21 13:07:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16498325765132904 | lossAlign: 0 +2025-09-21 13:07:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15368226170539856 | lossAlign: 0 +2025-09-21 13:07:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14997205138206482 | lossAlign: 0 +2025-09-21 13:07:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15293268859386444 | lossAlign: 0 +2025-09-21 13:07:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15859898924827576 | lossAlign: 0 +2025-09-21 13:07:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16420051455497742 | lossAlign: 0 +2025-09-21 13:08:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16892243921756744 | lossAlign: 0 +2025-09-21 13:08:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 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temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.155640110373497 | lossAlign: 0 +2025-09-21 13:08:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14755330979824066 | lossAlign: 0 +2025-09-21 13:08:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:08:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:08:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17732369899749756 | lossAlign: 0 +2025-09-21 13:08:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14436650276184082 | lossAlign: 0 +2025-09-21 13:08:26 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:08:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14451797306537628 | lossAlign: 0 +2025-09-21 13:08:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16990341246128082 | lossAlign: 0 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lossAlign: 0 +2025-09-21 13:08:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13491417467594147 | lossAlign: 0 +2025-09-21 13:08:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15165765583515167 | lossAlign: 0 +2025-09-21 13:08:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14777477085590363 | lossAlign: 0 +2025-09-21 13:08:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:08:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:08:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14153969287872314 | lossAlign: 0 +2025-09-21 13:08:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19545267522335052 | lossAlign: 0 +2025-09-21 13:08:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17119061946868896 | lossAlign: 0 +2025-09-21 13:08:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16248662769794464 | lossAlign: 0 +2025-09-21 13:09:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15416887402534485 | lossAlign: 0 +2025-09-21 13:09:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16941137611865997 | lossAlign: 0 +2025-09-21 13:09:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15704694390296936 | lossAlign: 0 +2025-09-21 13:09:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14746230840682983 | lossAlign: 0 +2025-09-21 13:09:07 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:09:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19580785930156708 | lossAlign: 0 +2025-09-21 13:09:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.190218985080719 | lossAlign: 0 +2025-09-21 13:09:11 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:09:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1287640780210495 | lossAlign: 0 +2025-09-21 13:09:12 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15796838700771332 | lossAlign: 0 +2025-09-21 13:09:15 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:09:15 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:09:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1578797847032547 | lossAlign: 0 +2025-09-21 13:09:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17896591126918793 | lossAlign: 0 +2025-09-21 13:09:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14839307963848114 | lossAlign: 0 +2025-09-21 13:09:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15902838110923767 | lossAlign: 0 +2025-09-21 13:09:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1532382071018219 | lossAlign: 0 +2025-09-21 13:09:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1902894526720047 | lossAlign: 0 +2025-09-21 13:09:27 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:09:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1588454246520996 | lossAlign: 0 +2025-09-21 13:09:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15364836156368256 | lossAlign: 0 +2025-09-21 13:09:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18270020186901093 | lossAlign: 0 +2025-09-21 13:09:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.158347025513649 | lossAlign: 0 +2025-09-21 13:09:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15133638679981232 | lossAlign: 0 +2025-09-21 13:09:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17465166747570038 | lossAlign: 0 +2025-09-21 13:09:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1612492799758911 | lossAlign: 0 +2025-09-21 13:09:41 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18816454708576202 | lossAlign: 0 +2025-09-21 13:09:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:09:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15910454094409943 | lossAlign: 0 +2025-09-21 13:09:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1595519483089447 | lossAlign: 0 +2025-09-21 13:09:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1853746920824051 | lossAlign: 0 +2025-09-21 13:09:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16392984986305237 | lossAlign: 0 +2025-09-21 13:09:52 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:09:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1502692550420761 | lossAlign: 0 +2025-09-21 13:09:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15926869213581085 | lossAlign: 0 +2025-09-21 13:09:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15661181509494781 | lossAlign: 0 +2025-09-21 13:09:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18237929046154022 | lossAlign: 0 +2025-09-21 13:10:00 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:10:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18057122826576233 | lossAlign: 0 +2025-09-21 13:10:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1744348704814911 | lossAlign: 0 +2025-09-21 13:10:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15449541807174683 | lossAlign: 0 +2025-09-21 13:10:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19380909204483032 | lossAlign: 0 +2025-09-21 13:10:08 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:10:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17115582525730133 | lossAlign: 0 +2025-09-21 13:10:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15463261306285858 | lossAlign: 0 +2025-09-21 13:10:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14330686628818512 | lossAlign: 0 +2025-09-21 13:10:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13558894395828247 | lossAlign: 0 +2025-09-21 13:10:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14172929525375366 | lossAlign: 0 +2025-09-21 13:10:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15940319001674652 | lossAlign: 0 +2025-09-21 13:10:20 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:10:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15450194478034973 | lossAlign: 0 +2025-09-21 13:10:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13290037214756012 | lossAlign: 0 +2025-09-21 13:10:24 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:10:24 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:10:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15377679467201233 | lossAlign: 0 +2025-09-21 13:10:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1519159972667694 | lossAlign: 0 +2025-09-21 13:10:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15599466860294342 | lossAlign: 0 +2025-09-21 13:10:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17011494934558868 | lossAlign: 0 +2025-09-21 13:10:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1670141965150833 | lossAlign: 0 +2025-09-21 13:10:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17683620750904083 | lossAlign: 0 +2025-09-21 13:10:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14419977366924286 | lossAlign: 0 +2025-09-21 13:10:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17944476008415222 | lossAlign: 0 +2025-09-21 13:10:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13186685740947723 | lossAlign: 0 +2025-09-21 13:10:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.142021045088768 | lossAlign: 0 +2025-09-21 13:10:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16494432091712952 | lossAlign: 0 +2025-09-21 13:10:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1512804925441742 | lossAlign: 0 +2025-09-21 13:10:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14728182554244995 | lossAlign: 0 +2025-09-21 13:10:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.141476571559906 | lossAlign: 0 +2025-09-21 13:10:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20326758921146393 | lossAlign: 0 +2025-09-21 13:10:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16496089100837708 | lossAlign: 0 +2025-09-21 13:10:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14776265621185303 | lossAlign: 0 +2025-09-21 13:10:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1744355410337448 | lossAlign: 0 +2025-09-21 13:11:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15527670085430145 | lossAlign: 0 +2025-09-21 13:11:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1497058868408203 | lossAlign: 0 +2025-09-21 13:11:05 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:11:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14217138290405273 | lossAlign: 0 +2025-09-21 13:11:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13861162960529327 | lossAlign: 0 +2025-09-21 13:11:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18235984444618225 | lossAlign: 0 +2025-09-21 13:11:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.21469561755657196 | lossAlign: 0 +2025-09-21 13:11:13 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:11:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13596457242965698 | lossAlign: 0 +2025-09-21 13:11:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19072723388671875 | lossAlign: 0 +2025-09-21 13:11:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15230128169059753 | lossAlign: 0 +2025-09-21 13:11:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1698521226644516 | lossAlign: 0 +2025-09-21 13:11:22 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:11:22 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:11:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15878422558307648 | lossAlign: 0 +2025-09-21 13:11:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17449063062667847 | lossAlign: 0 +2025-09-21 13:11:26 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:11:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14828573167324066 | lossAlign: 0 +2025-09-21 13:11:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15604445338249207 | lossAlign: 0 +2025-09-21 13:11:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16099418699741364 | lossAlign: 0 +2025-09-21 13:11:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2041453719139099 | lossAlign: 0 +2025-09-21 13:11:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18896251916885376 | lossAlign: 0 +2025-09-21 13:11:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15833157300949097 | lossAlign: 0 +2025-09-21 13:11:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.171976238489151 | lossAlign: 0 +2025-09-21 13:11:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15566076338291168 | lossAlign: 0 +2025-09-21 13:11:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18819117546081543 | lossAlign: 0 +2025-09-21 13:11:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.167893186211586 | lossAlign: 0 +2025-09-21 13:11:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18720564246177673 | lossAlign: 0 +2025-09-21 13:11:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20319391787052155 | lossAlign: 0 +2025-09-21 13:11:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:11:50 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:11:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14132660627365112 | lossAlign: 0 +2025-09-21 13:11:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14853252470493317 | lossAlign: 0 +2025-09-21 13:11:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15197955071926117 | lossAlign: 0 +2025-09-21 13:11:55 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17267443239688873 | lossAlign: 0 +2025-09-21 13:11:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:11:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17074744403362274 | lossAlign: 0 +2025-09-21 13:11:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16104039549827576 | lossAlign: 0 +2025-09-21 13:12:02 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:12:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16163679957389832 | lossAlign: 0 +2025-09-21 13:12:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14852093160152435 | lossAlign: 0 +2025-09-21 13:12:06 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:12:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13613499701023102 | lossAlign: 0 +2025-09-21 13:12:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16457965970039368 | lossAlign: 0 +2025-09-21 13:12:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15703131258487701 | lossAlign: 0 +2025-09-21 13:12:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17625489830970764 | lossAlign: 0 +2025-09-21 13:12:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1348653882741928 | lossAlign: 0 +2025-09-21 13:12:16 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14979365468025208 | lossAlign: 0 +2025-09-21 13:12:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:12:19 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:12:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1436978131532669 | lossAlign: 0 +2025-09-21 13:12:20 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14538951218128204 | lossAlign: 0 +2025-09-21 13:12:23 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:12:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14283668994903564 | lossAlign: 0 +2025-09-21 13:12:24 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16588599979877472 | lossAlign: 0 +2025-09-21 13:12:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15913279354572296 | lossAlign: 0 +2025-09-21 13:12:28 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14761397242546082 | lossAlign: 0 +2025-09-21 13:12:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16380254924297333 | lossAlign: 0 +2025-09-21 13:12:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16998137533664703 | lossAlign: 0 +2025-09-21 13:12:35 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:12:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2103167176246643 | lossAlign: 0 +2025-09-21 13:12:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18244953453540802 | lossAlign: 0 +2025-09-21 13:12:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15521807968616486 | lossAlign: 0 +2025-09-21 13:12:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1672264039516449 | lossAlign: 0 +2025-09-21 13:12:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16704854369163513 | lossAlign: 0 +2025-09-21 13:12:45 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19240590929985046 | lossAlign: 0 +2025-09-21 13:12:48 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:12:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15397746860980988 | lossAlign: 0 +2025-09-21 13:12:49 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15846537053585052 | lossAlign: 0 +2025-09-21 13:12:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16728417575359344 | lossAlign: 0 +2025-09-21 13:12:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20123203098773956 | lossAlign: 0 +2025-09-21 13:12:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14078181982040405 | lossAlign: 0 +2025-09-21 13:12:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15944167971611023 | lossAlign: 0 +2025-09-21 13:13:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1613805890083313 | lossAlign: 0 +2025-09-21 13:13:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16241948306560516 | lossAlign: 0 +2025-09-21 13:13:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19008153676986694 | lossAlign: 0 +2025-09-21 13:13:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15006621181964874 | lossAlign: 0 +2025-09-21 13:13:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1452508270740509 | lossAlign: 0 +2025-09-21 13:13:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1645168662071228 | lossAlign: 0 +2025-09-21 13:13:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15471386909484863 | lossAlign: 0 +2025-09-21 13:13:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16486120223999023 | lossAlign: 0 +2025-09-21 13:13:16 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:16 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18953895568847656 | lossAlign: 0 +2025-09-21 13:13:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16197052597999573 | lossAlign: 0 +2025-09-21 13:13:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13890691101551056 | lossAlign: 0 +2025-09-21 13:13:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15460678935050964 | lossAlign: 0 +2025-09-21 13:13:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16978459060192108 | lossAlign: 0 +2025-09-21 13:13:26 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1548556387424469 | lossAlign: 0 +2025-09-21 13:13:29 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.153579443693161 | lossAlign: 0 +2025-09-21 13:13:30 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1670255959033966 | lossAlign: 0 +2025-09-21 13:13:33 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:33 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1746387630701065 | lossAlign: 0 +2025-09-21 13:13:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1469581425189972 | lossAlign: 0 +2025-09-21 13:13:37 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1592129021883011 | lossAlign: 0 +2025-09-21 13:13:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15896596014499664 | lossAlign: 0 +2025-09-21 13:13:41 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1553584188222885 | lossAlign: 0 +2025-09-21 13:13:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15357525646686554 | lossAlign: 0 +2025-09-21 13:13:45 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1497614085674286 | lossAlign: 0 +2025-09-21 13:13:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15609890222549438 | lossAlign: 0 +2025-09-21 13:13:49 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17948836088180542 | lossAlign: 0 +2025-09-21 13:13:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18070662021636963 | lossAlign: 0 +2025-09-21 13:13:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18664370477199554 | lossAlign: 0 +2025-09-21 13:13:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19102522730827332 | lossAlign: 0 +2025-09-21 13:13:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:58 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:13:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15503722429275513 | lossAlign: 0 +2025-09-21 13:13:59 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1407461315393448 | lossAlign: 0 +2025-09-21 13:14:01 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:14:01 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:14:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15990880131721497 | lossAlign: 0 +2025-09-21 13:14:03 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13348597288131714 | lossAlign: 0 +2025-09-21 13:14:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.2132514864206314 | lossAlign: 0 +2025-09-21 13:14:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13049276173114777 | lossAlign: 0 +2025-09-21 13:14:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16346819698810577 | lossAlign: 0 +2025-09-21 13:14:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16020584106445312 | lossAlign: 0 +2025-09-21 13:14:14 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:14:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16923558712005615 | lossAlign: 0 +2025-09-21 13:14:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18643131852149963 | lossAlign: 0 +2025-09-21 13:14:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15961089730262756 | lossAlign: 0 +2025-09-21 13:14:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.12996943295001984 | lossAlign: 0 +2025-09-21 13:14:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1574702262878418 | lossAlign: 0 +2025-09-21 13:14:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1660461574792862 | lossAlign: 0 +2025-09-21 13:14:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16330869495868683 | lossAlign: 0 +2025-09-21 13:14:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1477687656879425 | lossAlign: 0 +2025-09-21 13:14:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14989808201789856 | lossAlign: 0 +2025-09-21 13:14:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1473173201084137 | lossAlign: 0 +2025-09-21 13:14:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1657659411430359 | lossAlign: 0 +2025-09-21 13:14:35 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17118550837039948 | lossAlign: 0 +2025-09-21 13:14:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16037189960479736 | lossAlign: 0 +2025-09-21 13:14:39 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17009426653385162 | lossAlign: 0 +2025-09-21 13:14:42 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:14:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1666002720594406 | lossAlign: 0 +2025-09-21 13:14:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.25323885679244995 | lossAlign: 0 +2025-09-21 13:14:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15925608575344086 | lossAlign: 0 +2025-09-21 13:14:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16230809688568115 | lossAlign: 0 +2025-09-21 13:14:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17461663484573364 | lossAlign: 0 +2025-09-21 13:14:52 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16777454316616058 | lossAlign: 0 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lossAlign: 0 +2025-09-21 13:15:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17564162611961365 | lossAlign: 0 +2025-09-21 13:15:12 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:15:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14410732686519623 | lossAlign: 0 +2025-09-21 13:15:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.168148472905159 | lossAlign: 0 +2025-09-21 13:15:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15424637496471405 | lossAlign: 0 +2025-09-21 13:15:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15467815101146698 | lossAlign: 0 +2025-09-21 13:15:20 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:15:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14303447306156158 | lossAlign: 0 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13:15:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1474151462316513 | lossAlign: 0 +2025-09-21 13:15:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17002445459365845 | lossAlign: 0 +2025-09-21 13:15:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15389622747898102 | lossAlign: 0 +2025-09-21 13:15:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16219180822372437 | lossAlign: 0 +2025-09-21 13:15:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16586299240589142 | lossAlign: 0 +2025-09-21 13:15:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15757711231708527 | lossAlign: 0 +2025-09-21 13:15:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16292248666286469 | lossAlign: 0 +2025-09-21 13:15:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1564483344554901 | lossAlign: 0 +2025-09-21 13:15:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14119704067707062 | lossAlign: 0 +2025-09-21 13:15:53 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:15:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16502997279167175 | lossAlign: 0 +2025-09-21 13:15:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15894334018230438 | lossAlign: 0 +2025-09-21 13:15:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1593652367591858 | lossAlign: 0 +2025-09-21 13:15:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19425754249095917 | lossAlign: 0 +2025-09-21 13:16:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18039387464523315 | lossAlign: 0 +2025-09-21 13:16:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1637250930070877 | lossAlign: 0 +2025-09-21 13:16:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15447422862052917 | lossAlign: 0 +2025-09-21 13:16:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1625778079032898 | lossAlign: 0 +2025-09-21 13:16:09 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:16:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1324823796749115 | lossAlign: 0 +2025-09-21 13:16:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13345761597156525 | lossAlign: 0 +2025-09-21 13:16:14 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:16:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16271598637104034 | lossAlign: 0 +2025-09-21 13:16:15 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15567654371261597 | lossAlign: 0 +2025-09-21 13:16:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14976678788661957 | lossAlign: 0 +2025-09-21 13:16:19 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17620623111724854 | lossAlign: 0 +2025-09-21 13:16:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14584673941135406 | lossAlign: 0 +2025-09-21 13:16:23 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16217917203903198 | lossAlign: 0 +2025-09-21 13:16:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16213110089302063 | lossAlign: 0 +2025-09-21 13:16:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15956911444664001 | lossAlign: 0 +2025-09-21 13:16:31 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1496707648038864 | lossAlign: 0 +2025-09-21 13:16:32 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20178139209747314 | lossAlign: 0 +2025-09-21 13:16:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20474781095981598 | lossAlign: 0 +2025-09-21 13:16:36 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16285446286201477 | lossAlign: 0 +2025-09-21 13:16:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15947246551513672 | lossAlign: 0 +2025-09-21 13:16:40 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1800912469625473 | lossAlign: 0 +2025-09-21 13:16:43 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:16:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1813381016254425 | lossAlign: 0 +2025-09-21 13:16:44 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1636020541191101 | lossAlign: 0 +2025-09-21 13:16:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17034301161766052 | lossAlign: 0 +2025-09-21 13:16:48 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16234952211380005 | lossAlign: 0 +2025-09-21 13:16:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15686072409152985 | lossAlign: 0 +2025-09-21 13:16:53 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17140477895736694 | lossAlign: 0 +2025-09-21 13:16:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18528695404529572 | lossAlign: 0 +2025-09-21 13:16:57 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15288519859313965 | lossAlign: 0 +2025-09-21 13:17:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16907161474227905 | lossAlign: 0 +2025-09-21 13:17:01 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15234509110450745 | lossAlign: 0 +2025-09-21 13:17:04 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:17:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15896916389465332 | lossAlign: 0 +2025-09-21 13:17:05 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20514613389968872 | lossAlign: 0 +2025-09-21 13:17:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1912066638469696 | lossAlign: 0 +2025-09-21 13:17:09 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1498400866985321 | lossAlign: 0 +2025-09-21 13:17:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16008684039115906 | lossAlign: 0 +2025-09-21 13:17:13 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14910301566123962 | lossAlign: 0 +2025-09-21 13:17:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16907182335853577 | lossAlign: 0 +2025-09-21 13:17:17 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16617198288440704 | lossAlign: 0 +2025-09-21 13:17:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14475665986537933 | lossAlign: 0 +2025-09-21 13:17:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19218379259109497 | lossAlign: 0 +2025-09-21 13:17:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15762099623680115 | lossAlign: 0 +2025-09-21 13:17:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1518431007862091 | lossAlign: 0 +2025-09-21 13:17:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1696307212114334 | lossAlign: 0 +2025-09-21 13:17:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14480853080749512 | lossAlign: 0 +2025-09-21 13:17:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1782984733581543 | lossAlign: 0 +2025-09-21 13:17:34 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15584200620651245 | lossAlign: 0 +2025-09-21 13:17:36 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:17:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16359376907348633 | lossAlign: 0 +2025-09-21 13:17:38 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16962188482284546 | lossAlign: 0 +2025-09-21 13:17:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15151247382164001 | lossAlign: 0 +2025-09-21 13:17:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15746761858463287 | lossAlign: 0 +2025-09-21 13:17:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13410519063472748 | lossAlign: 0 +2025-09-21 13:17:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1697215884923935 | lossAlign: 0 +2025-09-21 13:17:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1668883115053177 | lossAlign: 0 +2025-09-21 13:17:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.20504161715507507 | lossAlign: 0 +2025-09-21 13:17:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17098720371723175 | lossAlign: 0 +2025-09-21 13:17:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1706744283437729 | lossAlign: 0 +2025-09-21 13:17:57 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:17:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14220155775547028 | lossAlign: 0 +2025-09-21 13:17:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15043696761131287 | lossAlign: 0 +2025-09-21 13:18:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1489209681749344 | lossAlign: 0 +2025-09-21 13:18:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16066835820674896 | lossAlign: 0 +2025-09-21 13:18:05 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:18:05 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:18:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15476830303668976 | lossAlign: 0 +2025-09-21 13:18:06 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15801407396793365 | lossAlign: 0 +2025-09-21 13:18:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15087568759918213 | lossAlign: 0 +2025-09-21 13:18:10 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17863969504833221 | lossAlign: 0 +2025-09-21 13:18:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16819417476654053 | lossAlign: 0 +2025-09-21 13:18:14 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14527228474617004 | lossAlign: 0 +2025-09-21 13:18:17 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:18:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1604340672492981 | lossAlign: 0 +2025-09-21 13:18:18 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15341560542583466 | lossAlign: 0 +2025-09-21 13:18:21 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:18:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19829194247722626 | lossAlign: 0 +2025-09-21 13:18:22 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16099241375923157 | lossAlign: 0 +2025-09-21 13:18:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15014740824699402 | lossAlign: 0 +2025-09-21 13:18:27 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15646429359912872 | lossAlign: 0 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13:18:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.19039581716060638 | lossAlign: 0 +2025-09-21 13:18:43 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16196966171264648 | lossAlign: 0 +2025-09-21 13:18:46 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:18:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17932987213134766 | lossAlign: 0 +2025-09-21 13:18:47 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14801129698753357 | lossAlign: 0 +2025-09-21 13:18:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1595836728811264 | lossAlign: 0 +2025-09-21 13:18:51 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17011013627052307 | lossAlign: 0 +2025-09-21 13:18:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1458457112312317 | lossAlign: 0 +2025-09-21 13:18:56 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17778682708740234 | lossAlign: 0 +2025-09-21 13:19:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14305561780929565 | lossAlign: 0 +2025-09-21 13:19:00 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1518310308456421 | lossAlign: 0 +2025-09-21 13:19:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15421272814273834 | lossAlign: 0 +2025-09-21 13:19:04 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17667996883392334 | lossAlign: 0 +2025-09-21 13:19:07 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:19:08 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18052732944488525 | lossAlign: 0 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LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1691698133945465 | lossAlign: 0 +2025-09-21 13:19:21 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1572125107049942 | lossAlign: 0 +2025-09-21 13:19:24 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:19:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14344000816345215 | lossAlign: 0 +2025-09-21 13:19:25 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.13484035432338715 | lossAlign: 0 +2025-09-21 13:19:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15957880020141602 | lossAlign: 0 +2025-09-21 13:19:29 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15402701497077942 | lossAlign: 0 +2025-09-21 13:19:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14129753410816193 | lossAlign: 0 +2025-09-21 13:19:33 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1580290049314499 | lossAlign: 0 +2025-09-21 13:19:36 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:19:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1731310933828354 | lossAlign: 0 +2025-09-21 13:19:37 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.165500670671463 | lossAlign: 0 +2025-09-21 13:19:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1923198252916336 | lossAlign: 0 +2025-09-21 13:19:42 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15542057156562805 | lossAlign: 0 +2025-09-21 13:19:44 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:19:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16037501394748688 | lossAlign: 0 +2025-09-21 13:19:46 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16870799660682678 | lossAlign: 0 +2025-09-21 13:19:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1892596036195755 | lossAlign: 0 +2025-09-21 13:19:50 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14937724173069 | lossAlign: 0 +2025-09-21 13:19:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1837480217218399 | lossAlign: 0 +2025-09-21 13:19:54 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16035981476306915 | lossAlign: 0 +2025-09-21 13:19:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17658449709415436 | lossAlign: 0 +2025-09-21 13:19:58 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17597150802612305 | lossAlign: 0 +2025-09-21 13:20:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.1555940955877304 | lossAlign: 0 +2025-09-21 13:20:02 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.15507562458515167 | lossAlign: 0 +2025-09-21 13:20:06 | INFO | LVLM-Med | Wrong this box: [] +2025-09-21 13:20:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.14349164068698883 | lossAlign: 0 +2025-09-21 13:20:07 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.18467390537261963 | lossAlign: 0 +2025-09-21 13:20:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.17286933958530426 | lossAlign: 0 +2025-09-21 13:20:11 | INFO | LVLM-Med | Loss: + temperature: 0 | beta: 0 | alpha: 1.0 | decoder_output_loss: 0.16042138636112213 | lossAlign: 0 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