| --- |
| license: mit |
| base_model: almanach/camembert-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: NLP_projet |
| 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. --> |
|
|
| # NLP_projet |
| |
| This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5036 |
| - Precision: 0.9590 |
| - Recall: 0.9634 |
| - F1: 0.9612 |
| - Accuracy: 0.9636 |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 1.7382 | 1.0 | 955 | 0.7058 | 0.9442 | 0.9551 | 0.9496 | 0.9554 | |
| | 0.6625 | 2.0 | 1910 | 0.5036 | 0.9590 | 0.9634 | 0.9612 | 0.9636 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.39.3 |
| - Pytorch 2.2.2+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
| |
