04-20-14-12-55
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0027
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.6381 | 0.21 | 10 | 0.6152 | 0.8902 | 1.0 | 0.7273 | 0.8421 |
0.6424 | 0.42 | 20 | 0.5625 | 0.7073 | 1.0 | 0.2727 | 0.4286 |
0.6142 | 0.62 | 30 | 0.5137 | 0.6341 | 1.0 | 0.0909 | 0.1667 |
0.4652 | 0.83 | 40 | 0.4268 | 0.7561 | 1.0 | 0.3939 | 0.5652 |
0.3738 | 1.04 | 50 | 0.3096 | 0.9024 | 1.0 | 0.7576 | 0.8621 |
0.2406 | 1.25 | 60 | 0.1580 | 1.0 | 1.0 | 1.0 | 1.0 |
0.1364 | 1.46 | 70 | 0.0446 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0431 | 1.67 | 80 | 0.0142 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0133 | 1.88 | 90 | 0.0063 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0064 | 2.08 | 100 | 0.0041 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0045 | 2.29 | 110 | 0.0033 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0046 | 2.5 | 120 | 0.0029 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0037 | 2.71 | 130 | 0.0027 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0037 | 2.92 | 140 | 0.0027 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.13.3
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