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distilbert-base-uncased__hate_speech_offensive__train-8-8
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: 1.0005
- Accuracy: 0.518
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 |
|---|---|---|---|---|
| 1.1029 | 1.0 | 5 | 1.1295 | 0.0 |
| 1.0472 | 2.0 | 10 | 1.1531 | 0.0 |
| 1.054 | 3.0 | 15 | 1.1475 | 0.0 |
| 0.9366 | 4.0 | 20 | 1.1515 | 0.0 |
| 0.8698 | 5.0 | 25 | 1.1236 | 0.4 |
| 0.8148 | 6.0 | 30 | 1.0716 | 0.6 |
| 0.6884 | 7.0 | 35 | 1.0662 | 0.6 |
| 0.5641 | 8.0 | 40 | 1.0671 | 0.6 |
| 0.5 | 9.0 | 45 | 1.0282 | 0.6 |
| 0.3882 | 10.0 | 50 | 1.0500 | 0.6 |
| 0.3522 | 11.0 | 55 | 1.1381 | 0.6 |
| 0.2492 | 12.0 | 60 | 1.1278 | 0.6 |
| 0.2063 | 13.0 | 65 | 1.0731 | 0.6 |
| 0.1608 | 14.0 | 70 | 1.1339 | 0.6 |
| 0.1448 | 15.0 | 75 | 1.1892 | 0.6 |
| 0.0925 | 16.0 | 80 | 1.1840 | 0.6 |
| 0.0768 | 17.0 | 85 | 1.0608 | 0.6 |
| 0.0585 | 18.0 | 90 | 1.1073 | 0.6 |
| 0.0592 | 19.0 | 95 | 1.3134 | 0.6 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
