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questionAnswer3
This model is a fine-tuned version of deepset/bert-base-cased-squad2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.9120
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: 0.002
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
5.7468 | 1.0 | 3 | 3.9120 |
4.019 | 2.0 | 6 | 3.9120 |
3.9218 | 3.0 | 9 | 3.9120 |
3.9304 | 4.0 | 12 | 3.9120 |
3.9305 | 5.0 | 15 | 3.9120 |
3.9224 | 6.0 | 18 | 3.9120 |
3.9035 | 7.0 | 21 | 3.9120 |
3.954 | 8.0 | 24 | 3.9120 |
3.918 | 9.0 | 27 | 3.9120 |
3.9013 | 10.0 | 30 | 3.9120 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2