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distilbert-base-uncased-finetuned-natural-questions
This model is a fine-tuned version of distilbert-base-uncased on the natural_questions dataset. It achieves the following results on the evaluation set:
- Loss: 0.6267
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0532 | 1.0 | 5104 | 0.2393 |
| 1.8912 | 2.0 | 10208 | 0.2284 |
| 1.7854 | 3.0 | 15312 | 0.2357 |
| 1.6856 | 4.0 | 20416 | 0.2487 |
| 1.5918 | 5.0 | 25520 | 0.2743 |
| 1.5067 | 6.0 | 30624 | 0.2586 |
| 1.4323 | 7.0 | 35728 | 0.2763 |
| 1.365 | 8.0 | 40832 | 0.2753 |
| 1.3162 | 9.0 | 45936 | 0.3200 |
| 1.281 | 10.0 | 51040 | 0.3127 |
| 1.308 | 11.0 | 57104 | 0.2947 |
| 1.241 | 12.0 | 62208 | 0.2941 |
| 1.1391 | 13.0 | 67312 | 0.3103 |
| 1.0334 | 14.0 | 72416 | 0.3694 |
| 0.9538 | 15.0 | 77520 | 0.3658 |
| 0.8749 | 16.0 | 82624 | 0.4009 |
| 0.8154 | 17.0 | 87728 | 0.3672 |
| 0.7533 | 18.0 | 92832 | 0.3675 |
| 0.7079 | 19.0 | 97936 | 0.4611 |
| 0.6658 | 20.0 | 103040 | 0.4222 |
| 0.595 | 21.0 | 108144 | 0.4095 |
| 0.5765 | 22.0 | 113248 | 0.4400 |
| 0.5259 | 23.0 | 118352 | 0.5109 |
| 0.4804 | 24.0 | 123456 | 0.4711 |
| 0.4389 | 25.0 | 128560 | 0.5072 |
| 0.4034 | 26.0 | 133664 | 0.5363 |
| 0.374 | 27.0 | 138768 | 0.5460 |
| 0.3434 | 28.0 | 143872 | 0.5627 |
| 0.3181 | 29.0 | 148976 | 0.5657 |
| 0.2971 | 30.0 | 154080 | 0.5819 |
| 0.275 | 31.0 | 159184 | 0.5649 |
| 0.2564 | 32.0 | 164288 | 0.6087 |
| 0.2431 | 33.0 | 169392 | 0.6137 |
| 0.2289 | 34.0 | 174496 | 0.6123 |
| 0.2151 | 35.0 | 179600 | 0.5979 |
| 0.2041 | 36.0 | 184704 | 0.6196 |
| 0.1922 | 37.0 | 189808 | 0.6191 |
| 0.1852 | 38.0 | 194912 | 0.6313 |
| 0.1718 | 39.0 | 200016 | 0.6234 |
| 0.1718 | 39.81 | 204160 | 0.6267 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0
- Datasets 1.18.4
- Tokenizers 0.11.6
