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bert-18
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: 8.3340
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: 0.0001
- 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 |
|---|---|---|---|
| 11.2713 | 0.09 | 5 | 12.1606 |
| 11.199 | 0.18 | 10 | 11.9115 |
| 10.6074 | 0.27 | 15 | 11.6709 |
| 10.5475 | 0.36 | 20 | 11.4407 |
| 10.3761 | 0.45 | 25 | 11.2173 |
| 10.2166 | 0.55 | 30 | 11.0033 |
| 9.4143 | 0.64 | 35 | 10.7983 |
| 9.8307 | 0.73 | 40 | 10.6034 |
| 9.3026 | 0.82 | 45 | 10.4169 |
| 9.0636 | 0.91 | 50 | 10.2387 |
| 8.7689 | 1.0 | 55 | 10.0700 |
| 8.7969 | 1.09 | 60 | 9.9094 |
| 8.7596 | 1.18 | 65 | 9.7588 |
| 8.8433 | 1.27 | 70 | 9.6152 |
| 8.3576 | 1.36 | 75 | 9.4808 |
| 8.6226 | 1.45 | 80 | 9.3540 |
| 8.3176 | 1.55 | 85 | 9.2346 |
| 8.2174 | 1.64 | 90 | 9.1231 |
| 8.0514 | 1.73 | 95 | 9.0198 |
| 8.0813 | 1.82 | 100 | 8.9240 |
| 7.6971 | 1.91 | 105 | 8.8362 |
| 7.865 | 2.0 | 110 | 8.7562 |
| 7.7614 | 2.09 | 115 | 8.6834 |
| 7.6525 | 2.18 | 120 | 8.6179 |
| 7.7074 | 2.27 | 125 | 8.5593 |
| 7.7802 | 2.36 | 130 | 8.5073 |
| 7.4788 | 2.45 | 135 | 8.4625 |
| 7.6863 | 2.55 | 140 | 8.4245 |
| 7.3113 | 2.64 | 145 | 8.3934 |
| 7.6127 | 2.73 | 150 | 8.3692 |
| 7.471 | 2.82 | 155 | 8.3509 |
| 7.4979 | 2.91 | 160 | 8.3393 |
| 7.5977 | 3.0 | 165 | 8.3340 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
