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distilbert-base-uncased-finetuned-sqaud
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: 0.2831
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 |
|---|---|---|---|
| No log | 1.0 | 14 | 0.9851 |
| No log | 2.0 | 28 | 0.6955 |
| No log | 3.0 | 42 | 0.5781 |
| No log | 4.0 | 56 | 0.4548 |
| No log | 5.0 | 70 | 0.4208 |
| No log | 6.0 | 84 | 0.3592 |
| No log | 7.0 | 98 | 0.3422 |
| No log | 8.0 | 112 | 0.3424 |
| No log | 9.0 | 126 | 0.4046 |
| No log | 10.0 | 140 | 0.3142 |
| No log | 11.0 | 154 | 0.3262 |
| No log | 12.0 | 168 | 0.2879 |
| No log | 13.0 | 182 | 0.3376 |
| No log | 14.0 | 196 | 0.2870 |
| No log | 15.0 | 210 | 0.2984 |
| No log | 16.0 | 224 | 0.2807 |
| No log | 17.0 | 238 | 0.2889 |
| No log | 18.0 | 252 | 0.2877 |
| No log | 19.0 | 266 | 0.2820 |
| No log | 20.0 | 280 | 0.2831 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
