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distilbert-base-uncased__hate_speech_offensive__train-32-3
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: 0.8286
- Accuracy: 0.661
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 |
|---|---|---|---|---|
| 1.1041 | 1.0 | 19 | 1.0658 | 0.5 |
| 1.009 | 2.0 | 38 | 0.9892 | 0.7 |
| 0.7925 | 3.0 | 57 | 0.8516 | 0.7 |
| 0.5279 | 4.0 | 76 | 0.7877 | 0.65 |
| 0.2932 | 5.0 | 95 | 0.7592 | 0.65 |
| 0.1166 | 6.0 | 114 | 0.9437 | 0.65 |
| 0.044 | 7.0 | 133 | 1.0315 | 0.75 |
| 0.0197 | 8.0 | 152 | 1.3513 | 0.55 |
| 0.0126 | 9.0 | 171 | 1.1702 | 0.7 |
| 0.0083 | 10.0 | 190 | 1.2272 | 0.7 |
| 0.0068 | 11.0 | 209 | 1.2889 | 0.7 |
| 0.0059 | 12.0 | 228 | 1.3073 | 0.7 |
| 0.0052 | 13.0 | 247 | 1.3595 | 0.7 |
| 0.0041 | 14.0 | 266 | 1.4443 | 0.7 |
| 0.0038 | 15.0 | 285 | 1.4709 | 0.7 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
