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--- |
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library_name: transformers |
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license: mit |
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base_model: almanach/camembert-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: td2 |
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results: [] |
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language: |
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- fr |
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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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# td2 |
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TD2 - ESGI |
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# Ahmed Ennaifer & Sarra Chabane Chaouche |
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This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on the None dataset. |
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It achieves the following results on the evaluation set of train/test: |
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- Loss: 0.0128 |
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- Precision: 0.0 |
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- Recall: 0.0 |
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- F1: 0.0 |
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- Accuracy: 0.9983 |
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# The model got an accuracy of `0.998` on the seperate eval dataset : `test_fr` |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:| |
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| No log | 1.0 | 160 | 0.0455 | 0.0 | 0.0 | 0.0 | 0.9975 | |
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| No log | 2.0 | 320 | 0.0292 | 0.0 | 0.0 | 0.0 | 0.9981 | |
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| No log | 3.0 | 480 | 0.0224 | 0.0 | 0.0 | 0.0 | 0.9981 | |
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| 0.0837 | 4.0 | 640 | 0.0188 | 0.0 | 0.0 | 0.0 | 0.9981 | |
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| 0.0837 | 5.0 | 800 | 0.0166 | 0.0 | 0.0 | 0.0 | 0.9979 | |
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| 0.0837 | 6.0 | 960 | 0.0148 | 0.0 | 0.0 | 0.0 | 0.9981 | |
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| 0.0182 | 7.0 | 1120 | 0.0139 | 0.0 | 0.0 | 0.0 | 0.9982 | |
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| 0.0182 | 8.0 | 1280 | 0.0133 | 0.0 | 0.0 | 0.0 | 0.9981 | |
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| 0.0182 | 9.0 | 1440 | 0.0129 | 0.0 | 0.0 | 0.0 | 0.9982 | |
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| 0.0122 | 10.0 | 1600 | 0.0128 | 0.0 | 0.0 | 0.0 | 0.9983 | |
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### Framework versions |
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- Transformers 4.50.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.4.1 |
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- Tokenizers 0.21.1 |
