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bert-28
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: 11.6678
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|
| 11.2204 | 0.18 | 5 | 12.3027 |
| 10.9471 | 0.36 | 10 | 12.2255 |
| 11.0769 | 0.54 | 15 | 12.1528 |
| 10.8237 | 0.71 | 20 | 12.0849 |
| 10.6924 | 0.89 | 25 | 12.0233 |
| 10.5051 | 1.07 | 30 | 11.9672 |
| 10.6612 | 1.25 | 35 | 11.9154 |
| 10.5235 | 1.43 | 40 | 11.8683 |
| 10.4814 | 1.61 | 45 | 11.8262 |
| 10.5109 | 1.79 | 50 | 11.7882 |
| 10.623 | 1.96 | 55 | 11.7560 |
| 10.4358 | 2.14 | 60 | 11.7285 |
| 10.234 | 2.32 | 65 | 11.7056 |
| 10.2805 | 2.5 | 70 | 11.6881 |
| 10.6227 | 2.68 | 75 | 11.6760 |
| 10.2278 | 2.86 | 80 | 11.6678 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
