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bert-base-uncased
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: 0.1434
- F1 Score: 0.9670
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 Score |
---|---|---|---|---|
0.0991 | 1.0 | 873 | 0.1463 | 0.9619 |
0.0529 | 2.0 | 1746 | 0.1434 | 0.9670 |
0.0216 | 3.0 | 2619 | 0.1762 | 0.9659 |
0.0126 | 4.0 | 3492 | 0.2089 | 0.9652 |
0.0065 | 5.0 | 4365 | 0.2178 | 0.9628 |
0.0047 | 6.0 | 5238 | 0.2370 | 0.9652 |
0.0062 | 7.0 | 6111 | 0.2190 | 0.9668 |
0.0042 | 8.0 | 6984 | 0.2303 | 0.9666 |
0.0035 | 9.0 | 7857 | 0.2406 | 0.9682 |
0.0011 | 10.0 | 8730 | 0.2422 | 0.9687 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3