qamodel_distilbert
This model is a fine-tuned version of distilbert-base-cased-distilled-squad on the subjqa dataset. It achieves the following results on the evaluation set:
- Loss: 1.7950
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: 1e-06
- 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: 18
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.1563 | 1.0 | 81 | 2.6200 |
| 2.0431 | 2.0 | 162 | 2.1380 |
| 1.8432 | 3.0 | 243 | 2.0108 |
| 1.7601 | 4.0 | 324 | 1.9526 |
| 1.6957 | 5.0 | 405 | 1.9126 |
| 1.6477 | 6.0 | 486 | 1.8846 |
| 1.6173 | 7.0 | 567 | 1.8699 |
| 1.5799 | 8.0 | 648 | 1.8527 |
| 1.5749 | 9.0 | 729 | 1.8367 |
| 1.5422 | 10.0 | 810 | 1.8281 |
| 1.5353 | 11.0 | 891 | 1.8208 |
| 1.529 | 12.0 | 972 | 1.8116 |
| 1.5101 | 13.0 | 1053 | 1.8049 |
| 1.5005 | 14.0 | 1134 | 1.8018 |
| 1.4932 | 15.0 | 1215 | 1.8008 |
| 1.4895 | 16.0 | 1296 | 1.7976 |
| 1.4817 | 17.0 | 1377 | 1.7957 |
| 1.4695 | 18.0 | 1458 | 1.7950 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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