bert-hate-speech-test
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6291
- Accuracy: 0.7193
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6593 | 1.0 | 57 | 0.6316 | 0.6667 |
| 0.6008 | 2.0 | 114 | 0.6574 | 0.6667 |
| 0.4936 | 3.0 | 171 | 0.6291 | 0.7193 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cpu
- Datasets 4.0.0
- Tokenizers 0.23.1