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distilbert-qa-checkpoint-v2
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: 0.3141
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: 20
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.6564 | 1.0 | 658 | 0.3612 |
0.3397 | 2.0 | 1316 | 0.3361 |
0.2885 | 3.0 | 1974 | 0.3515 |
0.2407 | 4.0 | 2632 | 0.3672 |
0.2213 | 5.0 | 3290 | 0.3718 |
0.2197 | 6.0 | 3948 | 0.3967 |
0.1986 | 7.0 | 4606 | 0.4115 |
0.1932 | 8.0 | 5264 | 0.4152 |
0.19 | 9.0 | 5922 | 0.4208 |
0.1844 | 10.0 | 6580 | 0.4472 |
0.1824 | 11.0 | 7238 | 0.4466 |
0.1812 | 12.0 | 7896 | 0.2695 |
0.0078 | 13.0 | 8554 | 0.2824 |
0.0073 | 14.0 | 9212 | 0.2793 |
0.0048 | 15.0 | 9870 | 0.3107 |
0.0033 | 16.0 | 10528 | 0.3074 |
0.0022 | 17.0 | 11186 | 0.3073 |
0.0038 | 18.0 | 11844 | 0.3147 |
0.0013 | 19.0 | 12502 | 0.3160 |
0.0008 | 20.0 | 13160 | 0.3141 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3