model
This model is a fine-tuned version of distilbert-base-uncased-distilled-squad on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 2 | 1.5204 |
No log | 2.0 | 4 | 0.1924 |
No log | 3.0 | 6 | 0.0326 |
No log | 4.0 | 8 | 0.0087 |
No log | 5.0 | 10 | 0.0034 |
No log | 6.0 | 12 | 0.0017 |
No log | 7.0 | 14 | 0.0009 |
No log | 8.0 | 16 | 0.0005 |
No log | 9.0 | 18 | 0.0002 |
No log | 10.0 | 20 | 0.0001 |
No log | 11.0 | 22 | 0.0001 |
No log | 12.0 | 24 | 0.0000 |
No log | 13.0 | 26 | 0.0000 |
No log | 14.0 | 28 | 0.0000 |
No log | 15.0 | 30 | 0.0000 |
No log | 16.0 | 32 | 0.0000 |
No log | 17.0 | 34 | 0.0000 |
No log | 18.0 | 36 | 0.0000 |
No log | 19.0 | 38 | 0.0000 |
No log | 20.0 | 40 | 0.0000 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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