bert-base-uncased-qqp
This model is a fine-tuned version of bert-base-uncased on the GLUE QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.2829
- Accuracy: 0.9100
- F1: 0.8788
- Combined Score: 0.8944
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.2511 | 1.0 | 11371 | 0.2469 | 0.8969 | 0.8641 | 0.8805 |
| 0.1763 | 2.0 | 22742 | 0.2379 | 0.9071 | 0.8769 | 0.8920 |
| 0.1221 | 3.0 | 34113 | 0.2829 | 0.9100 | 0.8788 | 0.8944 |
Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1