distilbert-qa-checkpoint
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: 0.2294
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 | 179 | 0.2972 |
| No log | 2.0 | 358 | 0.1753 |
| 0.4638 | 3.0 | 537 | 0.1634 |
| 0.4638 | 4.0 | 716 | 0.1731 |
| 0.4638 | 5.0 | 895 | 0.1996 |
| 0.0607 | 6.0 | 1074 | 0.2229 |
| 0.0607 | 7.0 | 1253 | 0.2189 |
| 0.0607 | 8.0 | 1432 | 0.2097 |
| 0.0318 | 9.0 | 1611 | 0.2300 |
| 0.0318 | 10.0 | 1790 | 0.2294 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3