<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
distilbert-base-uncased__hate_speech_offensive__train-32-8
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: 0.9191
- Accuracy: 0.632
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 |
---|---|---|---|---|
1.1008 | 1.0 | 19 | 1.0877 | 0.4 |
1.0354 | 2.0 | 38 | 1.0593 | 0.35 |
0.8765 | 3.0 | 57 | 0.9722 | 0.5 |
0.6365 | 4.0 | 76 | 0.9271 | 0.55 |
0.3944 | 5.0 | 95 | 0.7852 | 0.5 |
0.2219 | 6.0 | 114 | 0.9360 | 0.55 |
0.126 | 7.0 | 133 | 1.0610 | 0.55 |
0.0389 | 8.0 | 152 | 1.0884 | 0.6 |
0.0191 | 9.0 | 171 | 1.3483 | 0.55 |
0.0108 | 10.0 | 190 | 1.4226 | 0.55 |
0.0082 | 11.0 | 209 | 1.4270 | 0.55 |
0.0065 | 12.0 | 228 | 1.5074 | 0.55 |
0.0059 | 13.0 | 247 | 1.5577 | 0.55 |
0.0044 | 14.0 | 266 | 1.5798 | 0.55 |
0.0042 | 15.0 | 285 | 1.6196 | 0.55 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3