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clasificador-hate_speech_offensive
This model is a fine-tuned version of bert-base-uncased on the hate_speech_offensive dataset. It achieves the following results on the evaluation set:
- Loss: 0.3191
- Accuracy: 0.9201
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3425 | 1.0 | 2479 | 0.2982 | 0.9157 |
| 0.2783 | 2.0 | 4958 | 0.2695 | 0.9179 |
| 0.2321 | 3.0 | 7437 | 0.3191 | 0.9201 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
