Model description
This model is a fine-tuned version of bert-base-uncased on this Kaggle dataset. It achieves the following results on the evaluation set:
- Loss: 0.0507
Intended uses
The model is intended to be used for detecting 6 labels of toxicity. The model takes in a comment as string and predicts the probabilities of the 6 types of toxicity (as float between 0 and 1)
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0525 | 1.0 | 1250 | 0.0482 |
| 0.037 | 2.0 | 2500 | 0.0445 |
| 0.0275 | 3.0 | 3750 | 0.0489 |
| 0.0188 | 4.0 | 5000 | 0.0491 |
| 0.0146 | 5.0 | 6250 | 0.0507 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3
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