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distilbert-base-uncased__hate_speech_offensive__train-16-0
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: 1.2707
- Accuracy: 0.517
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 |
|---|---|---|---|---|
| 1.0943 | 1.0 | 10 | 1.1095 | 0.3 |
| 1.0602 | 2.0 | 20 | 1.1086 | 0.4 |
| 1.0159 | 3.0 | 30 | 1.1165 | 0.4 |
| 0.9027 | 4.0 | 40 | 1.1377 | 0.4 |
| 0.8364 | 5.0 | 50 | 1.0126 | 0.5 |
| 0.6653 | 6.0 | 60 | 0.9298 | 0.5 |
| 0.535 | 7.0 | 70 | 0.9555 | 0.5 |
| 0.3713 | 8.0 | 80 | 0.8543 | 0.4 |
| 0.1633 | 9.0 | 90 | 0.9876 | 0.4 |
| 0.1069 | 10.0 | 100 | 0.8383 | 0.6 |
| 0.0591 | 11.0 | 110 | 0.8056 | 0.6 |
| 0.0344 | 12.0 | 120 | 0.8915 | 0.6 |
| 0.0265 | 13.0 | 130 | 0.8722 | 0.6 |
| 0.0196 | 14.0 | 140 | 1.0064 | 0.6 |
| 0.0158 | 15.0 | 150 | 1.0479 | 0.6 |
| 0.0128 | 16.0 | 160 | 1.0723 | 0.6 |
| 0.0121 | 17.0 | 170 | 1.0758 | 0.6 |
| 0.0093 | 18.0 | 180 | 1.1236 | 0.6 |
| 0.0085 | 19.0 | 190 | 1.1480 | 0.6 |
| 0.0084 | 20.0 | 200 | 1.1651 | 0.6 |
| 0.0077 | 21.0 | 210 | 1.1832 | 0.6 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
