medgemma-4b-it-sft-lora
This model is a fine-tuned version of unsloth/medgemma-4b-it-unsloth-bnb-4bit on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.9301
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.6808 | 0.08 | 2 | 5.7399 |
| 1.3744 | 0.16 | 4 | 4.9466 |
| 1.1947 | 0.24 | 6 | 4.3908 |
| 1.0718 | 0.32 | 8 | 3.9348 |
| 0.9593 | 0.4 | 10 | 3.5351 |
| 0.8604 | 0.48 | 12 | 3.1574 |
| 0.7709 | 0.56 | 14 | 2.7945 |
| 0.686 | 0.64 | 16 | 2.4974 |
| 0.6152 | 0.72 | 18 | 2.2769 |
| 0.5609 | 0.8 | 20 | 2.1125 |
| 0.5274 | 0.88 | 22 | 1.9960 |
| 0.4886 | 0.96 | 24 | 1.9301 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1
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Model tree for yloa/medgemma-4b-it-sft-lora
Base model
google/gemma-3-4b-pt
Finetuned
google/medgemma-4b-pt
Finetuned
google/medgemma-4b-it
Quantized
unsloth/medgemma-4b-it-unsloth-bnb-4bit