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hateBERT-finetuned
This model is a fine-tuned version of GroNLP/hateBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7774
- Accuracy: 0.7967
- F1: 0.8416
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: 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4449 | 1.0 | 1548 | 0.4935 | 0.7909 | 0.8432 |
| 0.3465 | 2.0 | 3096 | 0.5296 | 0.7944 | 0.8375 |
| 0.2789 | 3.0 | 4644 | 0.7774 | 0.7967 | 0.8416 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.12.1+cu113
- Datasets 1.18.3
- Tokenizers 0.13.2
