qa_model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2864
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 |
---|---|---|---|
No log | 1.0 | 403 | 1.6619 |
2.4962 | 2.0 | 806 | 1.5064 |
1.3281 | 3.0 | 1209 | 1.5355 |
0.943 | 4.0 | 1612 | 1.6105 |
0.6258 | 5.0 | 2015 | 1.7803 |
0.6258 | 6.0 | 2418 | 1.8905 |
0.3992 | 7.0 | 2821 | 2.0605 |
0.2949 | 8.0 | 3224 | 2.2018 |
0.2103 | 9.0 | 3627 | 2.2359 |
0.1716 | 10.0 | 4030 | 2.2864 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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