| --- |
| library_name: transformers |
| license: mit |
| base_model: camembert-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: camembert-math-classification |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # camembert-math-classification |
|
|
| This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0166 |
| - F1 Macro: 0.9987 |
| - F1 Weighted: 0.9987 |
| - F1 Correct: 1.0 |
| - F1 Partiel: 0.9980 |
| - F1 Incorrect: 0.9980 |
| - Accuracy: 0.9987 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - 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_steps: 0.1 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | F1 Correct | F1 Partiel | F1 Incorrect | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:----------:|:----------:|:------------:|:--------:| |
| | 0.6561 | 1.0 | 184 | 0.8086 | 0.4912 | 0.4912 | 0.8169 | 0.0204 | 0.6364 | 0.5675 | |
| | 0.1997 | 2.0 | 368 | 0.1530 | 0.9669 | 0.9669 | 0.9902 | 0.9513 | 0.9592 | 0.9669 | |
| | 0.0648 | 3.0 | 552 | 0.0360 | 0.9960 | 0.9960 | 1.0 | 0.9940 | 0.9941 | 0.9960 | |
| | 0.0261 | 4.0 | 736 | 0.0227 | 0.9974 | 0.9974 | 0.9980 | 0.9960 | 0.9980 | 0.9974 | |
| | 0.0147 | 5.0 | 920 | 0.0166 | 0.9987 | 0.9987 | 1.0 | 0.9980 | 0.9980 | 0.9987 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 5.0.0 |
| - Tokenizers 0.22.2 |
|
|
