| --- |
| 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: distilbert_toxic |
| 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. --> |
|
|
| # distilbert_toxic |
| |
| 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: 0.5048 |
| - Accuracy: 0.8612 |
| - Precision: 0.8469 |
| - Recall: 0.8195 |
| - F1: 0.8330 |
| |
| ## 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: 3407 |
| - 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.2971 | 1.0 | 4767 | 0.3258 | 0.8675 | 0.8643 | 0.8140 | 0.8384 | |
| | 0.2798 | 2.0 | 9534 | 0.3120 | 0.8708 | 0.8452 | 0.8498 | 0.8475 | |
| | 0.1481 | 3.0 | 14301 | 0.3898 | 0.8681 | 0.8466 | 0.8399 | 0.8432 | |
| | 0.1161 | 4.0 | 19068 | 0.5048 | 0.8612 | 0.8469 | 0.8195 | 0.8330 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.0 |
| |
