bert-covidqa-1
This model is a fine-tuned version of deepset/bert-base-cased-squad2 on the covid_qa_deepset dataset. It achieves the following results on the evaluation set:
- Loss: 0.4528
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: 3e-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: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.0353 | 0.04 | 5 | 0.7327 |
1.1116 | 0.09 | 10 | 0.5674 |
0.8086 | 0.13 | 15 | 0.5025 |
0.814 | 0.18 | 20 | 0.5620 |
0.4168 | 0.22 | 25 | 0.6628 |
0.7069 | 0.26 | 30 | 0.5637 |
0.4168 | 0.31 | 35 | 0.4855 |
0.5636 | 0.35 | 40 | 0.4708 |
0.398 | 0.39 | 45 | 0.4712 |
0.4681 | 0.44 | 50 | 0.5235 |
0.34 | 0.48 | 55 | 0.5863 |
0.2484 | 0.53 | 60 | 0.6422 |
0.4526 | 0.57 | 65 | 0.6614 |
0.2941 | 0.61 | 70 | 0.6210 |
0.7383 | 0.66 | 75 | 0.5334 |
0.7337 | 0.7 | 80 | 0.4612 |
0.4082 | 0.75 | 85 | 0.4447 |
0.3517 | 0.79 | 90 | 0.4429 |
0.341 | 0.83 | 95 | 0.4446 |
0.2751 | 0.88 | 100 | 0.4536 |
0.4916 | 0.92 | 105 | 0.4566 |
0.4895 | 0.96 | 110 | 0.4528 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for hung200504/bert-covidqa-1
Base model
deepset/bert-base-cased-squad2