test-bert
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: 6.0267
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: 3e-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: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
5.8219 | 0.09 | 5 | 5.9435 |
4.9256 | 0.18 | 10 | 6.1109 |
4.3213 | 0.27 | 15 | 5.7204 |
3.5947 | 0.36 | 20 | 5.7525 |
3.0974 | 0.45 | 25 | 5.6447 |
2.7481 | 0.55 | 30 | 5.2776 |
2.207 | 0.64 | 35 | 5.3963 |
1.8922 | 0.73 | 40 | 5.4622 |
1.7034 | 0.82 | 45 | 5.3710 |
1.4313 | 0.91 | 50 | 5.3449 |
1.0748 | 1.0 | 55 | 5.3580 |
1.0215 | 1.09 | 60 | 5.4713 |
0.7634 | 1.18 | 65 | 5.5980 |
0.7535 | 1.27 | 70 | 5.6049 |
0.6063 | 1.36 | 75 | 5.5830 |
0.4824 | 1.45 | 80 | 5.6753 |
0.48 | 1.55 | 85 | 5.7216 |
0.4884 | 1.64 | 90 | 5.7817 |
0.5813 | 1.73 | 95 | 5.9427 |
0.4287 | 1.82 | 100 | 6.0148 |
0.4061 | 1.91 | 105 | 5.8752 |
0.55 | 2.0 | 110 | 5.8723 |
0.4631 | 2.09 | 115 | 5.8288 |
0.2987 | 2.18 | 120 | 5.8808 |
0.3359 | 2.27 | 125 | 5.8884 |
0.3002 | 2.36 | 130 | 5.9442 |
0.299 | 2.45 | 135 | 5.9331 |
0.3393 | 2.55 | 140 | 5.9454 |
0.2656 | 2.64 | 145 | 5.9894 |
0.3582 | 2.73 | 150 | 6.0142 |
0.2111 | 2.82 | 155 | 6.0329 |
0.2574 | 2.91 | 160 | 6.0304 |
0.2471 | 3.0 | 165 | 6.0267 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
google-bert/bert-base-cased