| library_name: transformers | |
| license: mit | |
| base_model: almanach/camembert-base | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| model-index: | |
| - name: bert-small-paragraph-classifier | |
| 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. --> | |
| # bert-small-paragraph-classifier | |
| This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1045 | |
| - Accuracy: 0.9983 | |
| - Precision: 0.9983 | |
| - Recall: 0.9983 | |
| - F1: 0.9983 | |
| ## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | |
| | No log | 1.0 | 338 | 0.1045 | 0.9983 | 0.9983 | 0.9983 | 0.9983 | | |
| | 0.4417 | 2.0 | 676 | 0.0408 | 0.9983 | 0.9983 | 0.9983 | 0.9983 | | |
| | 0.0461 | 3.0 | 1014 | 0.0291 | 0.9983 | 0.9983 | 0.9983 | 0.9983 | | |
| ### Framework versions | |
| - Transformers 4.53.1 | |
| - Pytorch 2.7.1 | |
| - Datasets 3.6.0 | |
| - Tokenizers 0.21.2 | |