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indobert-abusive-language-classifier
This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1613
- Train Sparse Categorical Accuracy: 0.9417
- Validation Loss: 0.2973
- Validation Sparse Categorical Accuracy: 0.8857
- Epoch: 2
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:
- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|---|---|---|---|---|
| 0.4496 | 0.7811 | 0.3146 | 0.8671 | 0 |
| 0.2437 | 0.9026 | 0.2959 | 0.8888 | 1 |
| 0.1613 | 0.9417 | 0.2973 | 0.8857 | 2 |
Framework versions
- Transformers 4.30.2
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3
