test-bert-2
This model is a fine-tuned version of deepset/bert-base-cased-squad2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 11.9673
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: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
10.9875 | 0.09 | 5 | 12.2820 |
10.8852 | 0.18 | 10 | 12.2237 |
10.4256 | 0.27 | 15 | 12.1709 |
10.7823 | 0.36 | 20 | 12.1247 |
10.6526 | 0.45 | 25 | 12.0841 |
10.7789 | 0.55 | 30 | 12.0501 |
10.1529 | 0.64 | 35 | 12.0217 |
10.0756 | 0.73 | 40 | 11.9991 |
10.4683 | 0.82 | 45 | 11.9829 |
10.2829 | 0.91 | 50 | 11.9721 |
10.5809 | 1.0 | 55 | 11.9673 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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