| --- |
| library_name: transformers |
| license: mit |
| base_model: FacebookAI/xlm-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: ToxicClassification2.0 |
| 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. --> |
|
|
| # ToxicClassification2.0 |
|
|
| This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7477 |
| - Accuracy: 0.8677 |
|
|
| ## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.4987 | 1.0 | 970 | 0.3175 | 0.8598 | |
| | 0.3342 | 2.0 | 1940 | 0.3325 | 0.8692 | |
| | 0.2808 | 3.0 | 2910 | 0.3273 | 0.8675 | |
| | 0.2514 | 4.0 | 3880 | 0.3878 | 0.8652 | |
| | 0.2075 | 5.0 | 4850 | 0.4068 | 0.8611 | |
| | 0.1887 | 6.0 | 5820 | 0.5277 | 0.8692 | |
| | 0.1641 | 7.0 | 6790 | 0.6208 | 0.8662 | |
| | 0.1419 | 8.0 | 7760 | 0.6979 | 0.8698 | |
| | 0.1150 | 9.0 | 8730 | 0.7489 | 0.8673 | |
| | 0.1005 | 10.0 | 9700 | 0.7477 | 0.8677 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.13.1 |
| - Pytorch 2.11.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
