uroptest2
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1950
- Precision: 0.4434
- Recall: 0.4290
- F1: 0.4361
- Accuracy: 0.9699
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0425 | 1.0 | 690 | 0.1567 | 0.3439 | 0.4198 | 0.3780 | 0.9637 |
0.0367 | 2.0 | 1380 | 0.1876 | 0.4529 | 0.3565 | 0.3990 | 0.9694 |
0.0251 | 3.0 | 2070 | 0.1603 | 0.3693 | 0.4599 | 0.4096 | 0.9662 |
0.0213 | 4.0 | 2760 | 0.1659 | 0.3842 | 0.4120 | 0.3976 | 0.9675 |
0.0166 | 5.0 | 3450 | 0.1732 | 0.3975 | 0.4429 | 0.4190 | 0.9677 |
0.0104 | 6.0 | 4140 | 0.1686 | 0.3871 | 0.4182 | 0.4021 | 0.9683 |
0.0105 | 7.0 | 4830 | 0.1809 | 0.4205 | 0.3920 | 0.4058 | 0.9688 |
0.0064 | 8.0 | 5520 | 0.1914 | 0.4452 | 0.4074 | 0.4255 | 0.9702 |
0.0047 | 9.0 | 6210 | 0.1908 | 0.4310 | 0.4244 | 0.4277 | 0.9696 |
0.004 | 10.0 | 6900 | 0.1950 | 0.4434 | 0.4290 | 0.4361 | 0.9699 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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