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bert-16
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: 10.2625
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: 5e-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 |
|---|---|---|---|
| 11.3013 | 0.09 | 5 | 12.2645 |
| 11.351 | 0.18 | 10 | 12.1394 |
| 10.8708 | 0.27 | 15 | 12.0185 |
| 10.9286 | 0.36 | 20 | 11.9023 |
| 10.8502 | 0.45 | 25 | 11.7895 |
| 10.806 | 0.55 | 30 | 11.6807 |
| 10.0507 | 0.64 | 35 | 11.5771 |
| 10.6057 | 0.73 | 40 | 11.4770 |
| 10.1224 | 0.82 | 45 | 11.3818 |
| 9.9648 | 0.91 | 50 | 11.2900 |
| 9.7027 | 1.0 | 55 | 11.2029 |
| 9.8434 | 1.09 | 60 | 11.1193 |
| 9.8999 | 1.18 | 65 | 11.0406 |
| 10.0717 | 1.27 | 70 | 10.9654 |
| 9.5874 | 1.36 | 75 | 10.8939 |
| 9.9629 | 1.45 | 80 | 10.8264 |
| 9.6759 | 1.55 | 85 | 10.7628 |
| 9.6001 | 1.64 | 90 | 10.7023 |
| 9.4276 | 1.73 | 95 | 10.6462 |
| 9.5867 | 1.82 | 100 | 10.5940 |
| 9.1448 | 1.91 | 105 | 10.5456 |
| 9.4274 | 2.0 | 110 | 10.5012 |
| 9.3621 | 2.09 | 115 | 10.4610 |
| 9.1924 | 2.18 | 120 | 10.4240 |
| 9.318 | 2.27 | 125 | 10.3911 |
| 9.4253 | 2.36 | 130 | 10.3618 |
| 9.0476 | 2.45 | 135 | 10.3361 |
| 9.3817 | 2.55 | 140 | 10.3147 |
| 8.9517 | 2.64 | 145 | 10.2968 |
| 9.4026 | 2.73 | 150 | 10.2828 |
| 9.1891 | 2.82 | 155 | 10.2723 |
| 9.1735 | 2.91 | 160 | 10.2654 |
| 9.3527 | 3.0 | 165 | 10.2625 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
