my_awesome_qa_model
This model is a fine-tuned version of bert-base-uncased on the squad dataset. It achieves the following results on the evaluation set:
- Loss: 0.0082
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: 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: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.5682 | 1.0 | 1250 | 0.5403 |
0.7379 | 2.0 | 2500 | 0.3208 |
0.4839 | 3.0 | 3750 | 0.1690 |
0.3227 | 4.0 | 5000 | 0.0984 |
0.2188 | 5.0 | 6250 | 0.0498 |
0.1484 | 6.0 | 7500 | 0.0341 |
0.1065 | 7.0 | 8750 | 0.0199 |
0.0796 | 8.0 | 10000 | 0.0127 |
0.0599 | 9.0 | 11250 | 0.0093 |
0.0484 | 10.0 | 12500 | 0.0082 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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