bert-base-uncased-finetuned-QnA-v1
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7610
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: 8
- 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 | 39 | 3.3668 |
| No log | 2.0 | 78 | 3.2134 |
| No log | 3.0 | 117 | 3.1685 |
| No log | 4.0 | 156 | 3.1042 |
| No log | 5.0 | 195 | 3.1136 |
| No log | 6.0 | 234 | 2.9051 |
| No log | 7.0 | 273 | 2.9077 |
| No log | 8.0 | 312 | 2.9774 |
| No log | 9.0 | 351 | 2.9321 |
| No log | 10.0 | 390 | 2.9501 |
| No log | 11.0 | 429 | 2.8544 |
| No log | 12.0 | 468 | 2.8761 |
| 3.0255 | 13.0 | 507 | 2.8152 |
| 3.0255 | 14.0 | 546 | 2.8046 |
| 3.0255 | 15.0 | 585 | 2.6979 |
| 3.0255 | 16.0 | 624 | 2.6379 |
| 3.0255 | 17.0 | 663 | 2.7091 |
| 3.0255 | 18.0 | 702 | 2.6914 |
| 3.0255 | 19.0 | 741 | 2.7403 |
| 3.0255 | 20.0 | 780 | 2.7479 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3