question_tax_indo
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0121
- F1: 0.9966
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 78 | 0.3959 | 0.9280 |
| 1.4775 | 2.0 | 156 | 0.2570 | 0.9836 |
| 0.3383 | 3.0 | 234 | 0.2211 | 0.9721 |
| 0.2629 | 4.0 | 312 | 0.1342 | 0.9902 |
| 0.2629 | 5.0 | 390 | 0.1120 | 0.9888 |
| 0.1931 | 6.0 | 468 | 0.0608 | 0.9935 |
| 0.1247 | 7.0 | 546 | 0.0326 | 0.9935 |
| 0.0905 | 8.0 | 624 | 0.0176 | 0.9954 |
| 0.0583 | 9.0 | 702 | 0.0156 | 0.9966 |
| 0.0583 | 10.0 | 780 | 0.0121 | 0.9966 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
google-bert/bert-base-uncased