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distilbert-base-uncased__hate_speech_offensive__train-32-4
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7384
- Accuracy: 0.724
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1013 | 1.0 | 19 | 1.0733 | 0.55 |
| 1.0226 | 2.0 | 38 | 1.0064 | 0.65 |
| 0.8539 | 3.0 | 57 | 0.8758 | 0.75 |
| 0.584 | 4.0 | 76 | 0.6941 | 0.7 |
| 0.2813 | 5.0 | 95 | 0.5151 | 0.7 |
| 0.1122 | 6.0 | 114 | 0.4351 | 0.8 |
| 0.0432 | 7.0 | 133 | 0.4896 | 0.85 |
| 0.0199 | 8.0 | 152 | 0.5391 | 0.85 |
| 0.0126 | 9.0 | 171 | 0.5200 | 0.85 |
| 0.0085 | 10.0 | 190 | 0.5622 | 0.85 |
| 0.0069 | 11.0 | 209 | 0.5950 | 0.85 |
| 0.0058 | 12.0 | 228 | 0.6015 | 0.85 |
| 0.0053 | 13.0 | 247 | 0.6120 | 0.85 |
| 0.0042 | 14.0 | 266 | 0.6347 | 0.85 |
| 0.0039 | 15.0 | 285 | 0.6453 | 0.85 |
| 0.0034 | 16.0 | 304 | 0.6660 | 0.85 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
