| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: distilbert/distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: cyberbtoxic-distilbert |
| | 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. --> |
| |
|
| | # cyberbtoxic-distilbert |
| |
|
| | This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3306 |
| | - Accuracy: 0.8695 |
| | - Precision: 0.8501 |
| | - Recall: 0.8971 |
| | - F1: 0.8730 |
| |
|
| | ## 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: 32 |
| | - 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: cosine |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 4 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 0.2846 | 1.0 | 4024 | 0.3352 | 0.8556 | 0.8382 | 0.8812 | 0.8592 | |
| | | 0.3027 | 2.0 | 8048 | 0.3306 | 0.8695 | 0.8501 | 0.8971 | 0.8730 | |
| | | 0.2062 | 3.0 | 12072 | 0.4010 | 0.8650 | 0.8609 | 0.8707 | 0.8658 | |
| | | 0.1604 | 4.0 | 16096 | 0.5293 | 0.8643 | 0.8547 | 0.8777 | 0.8660 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.56.1 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.0 |
| |
|
