distilbert-base-uncased__hate_speech_offensive__train-8-7
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: 1.1206
- Accuracy: 0.0555
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 |
---|---|---|---|---|
1.1186 | 1.0 | 5 | 1.1631 | 0.0 |
1.058 | 2.0 | 10 | 1.1986 | 0.0 |
1.081 | 3.0 | 15 | 1.2111 | 0.0 |
1.0118 | 4.0 | 20 | 1.2373 | 0.0 |
0.9404 | 5.0 | 25 | 1.2645 | 0.0 |
0.9146 | 6.0 | 30 | 1.3258 | 0.0 |
0.8285 | 7.0 | 35 | 1.3789 | 0.0 |
0.6422 | 8.0 | 40 | 1.3783 | 0.0 |
0.6156 | 9.0 | 45 | 1.3691 | 0.0 |
0.5321 | 10.0 | 50 | 1.3693 | 0.0 |
0.4504 | 11.0 | 55 | 1.4000 | 0.0 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
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