results
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: 0.1907
- F1: 0.9733
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 | 1.1812 | 0.7897 |
| 2.0042 | 2.0 | 156 | 0.9908 | 0.8857 |
| 1.1321 | 3.0 | 234 | 0.8354 | 0.9232 |
| 0.9122 | 4.0 | 312 | 0.7058 | 0.9286 |
| 0.9122 | 5.0 | 390 | 0.5304 | 0.9416 |
| 0.7847 | 6.0 | 468 | 0.4106 | 0.9592 |
| 0.606 | 7.0 | 546 | 0.3228 | 0.9575 |
| 0.4678 | 8.0 | 624 | 0.2596 | 0.9720 |
| 0.39 | 9.0 | 702 | 0.1826 | 0.9728 |
| 0.39 | 10.0 | 780 | 0.1907 | 0.9733 |
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