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distilbert-base-uncased__hate_speech_offensive__train-8-3
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: 0.9681
- Accuracy: 0.549
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 |
|---|---|---|---|---|
| 1.1073 | 1.0 | 5 | 1.1393 | 0.0 |
| 1.0392 | 2.0 | 10 | 1.1729 | 0.0 |
| 1.0302 | 3.0 | 15 | 1.1694 | 0.2 |
| 0.9176 | 4.0 | 20 | 1.1846 | 0.2 |
| 0.8339 | 5.0 | 25 | 1.1663 | 0.2 |
| 0.7533 | 6.0 | 30 | 1.1513 | 0.4 |
| 0.6327 | 7.0 | 35 | 1.1474 | 0.4 |
| 0.4402 | 8.0 | 40 | 1.1385 | 0.4 |
| 0.3752 | 9.0 | 45 | 1.0965 | 0.2 |
| 0.3448 | 10.0 | 50 | 1.0357 | 0.2 |
| 0.2582 | 11.0 | 55 | 1.0438 | 0.2 |
| 0.1903 | 12.0 | 60 | 1.0561 | 0.2 |
| 0.1479 | 13.0 | 65 | 1.0569 | 0.2 |
| 0.1129 | 14.0 | 70 | 1.0455 | 0.2 |
| 0.1071 | 15.0 | 75 | 1.0416 | 0.4 |
| 0.0672 | 16.0 | 80 | 1.1164 | 0.4 |
| 0.0561 | 17.0 | 85 | 1.1846 | 0.6 |
| 0.0463 | 18.0 | 90 | 1.2040 | 0.6 |
| 0.0431 | 19.0 | 95 | 1.2078 | 0.6 |
| 0.0314 | 20.0 | 100 | 1.2368 | 0.6 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
