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--- |
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library_name: peft |
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license: mit |
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base_model: xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: emotion-model2_0 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# emotion-model2_0 |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9084 |
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- Accuracy: 0.6936 |
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- F1: 0.6742 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.3859 | 1.0 | 59 | 1.3517 | 0.3532 | 0.3095 | |
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| 1.3202 | 2.0 | 118 | 1.2139 | 0.4638 | 0.3687 | |
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| 1.2606 | 3.0 | 177 | 1.1094 | 0.4851 | 0.3847 | |
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| 1.1821 | 4.0 | 236 | 1.0527 | 0.6213 | 0.6134 | |
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| 1.1665 | 5.0 | 295 | 0.9899 | 0.6638 | 0.6531 | |
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| 1.0941 | 6.0 | 354 | 0.9975 | 0.6043 | 0.5800 | |
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| 1.0943 | 7.0 | 413 | 0.9871 | 0.6085 | 0.5815 | |
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| 1.0671 | 8.0 | 472 | 0.9084 | 0.6936 | 0.6742 | |
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| 1.0401 | 9.0 | 531 | 0.9085 | 0.6681 | 0.6488 | |
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| 1.0221 | 10.0 | 590 | 0.9170 | 0.6681 | 0.6488 | |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.52.4 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
