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my_qa_model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5865
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: 0.0002
- 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 96 | 0.6101 |
| No log | 2.0 | 192 | 0.3681 |
| No log | 3.0 | 288 | 0.3647 |
| No log | 4.0 | 384 | 0.3718 |
| No log | 5.0 | 480 | 0.3506 |
| 0.4973 | 6.0 | 576 | 0.3861 |
| 0.4973 | 7.0 | 672 | 0.4109 |
| 0.4973 | 8.0 | 768 | 0.5558 |
| 0.4973 | 9.0 | 864 | 0.5509 |
| 0.4973 | 10.0 | 960 | 0.4134 |
| 0.1005 | 11.0 | 1056 | 0.4974 |
| 0.1005 | 12.0 | 1152 | 0.5251 |
| 0.1005 | 13.0 | 1248 | 0.6089 |
| 0.1005 | 14.0 | 1344 | 0.5672 |
| 0.1005 | 15.0 | 1440 | 0.5865 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
