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distilbert-base-uncased__hate_speech_offensive__train-16-1
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: 1.0424
- Accuracy: 0.5355
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 |
|---|---|---|---|---|
| 1.0989 | 1.0 | 10 | 1.1049 | 0.1 |
| 1.0641 | 2.0 | 20 | 1.0768 | 0.3 |
| 0.9742 | 3.0 | 30 | 1.0430 | 0.4 |
| 0.8765 | 4.0 | 40 | 1.0058 | 0.4 |
| 0.6979 | 5.0 | 50 | 0.8488 | 0.7 |
| 0.563 | 6.0 | 60 | 0.7221 | 0.7 |
| 0.4135 | 7.0 | 70 | 0.6587 | 0.8 |
| 0.2509 | 8.0 | 80 | 0.5577 | 0.7 |
| 0.0943 | 9.0 | 90 | 0.5840 | 0.7 |
| 0.0541 | 10.0 | 100 | 0.6959 | 0.7 |
| 0.0362 | 11.0 | 110 | 0.6884 | 0.6 |
| 0.0254 | 12.0 | 120 | 0.9263 | 0.6 |
| 0.0184 | 13.0 | 130 | 0.7992 | 0.6 |
| 0.0172 | 14.0 | 140 | 0.7351 | 0.6 |
| 0.0131 | 15.0 | 150 | 0.7664 | 0.6 |
| 0.0117 | 16.0 | 160 | 0.8262 | 0.6 |
| 0.0101 | 17.0 | 170 | 0.8839 | 0.6 |
| 0.0089 | 18.0 | 180 | 0.9018 | 0.6 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
