roberta-base-squad2-ta-qna-roberta10e
This model is a fine-tuned version of deepset/roberta-base-squad2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2952
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: 3e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 87 | 0.5890 |
| No log | 2.0 | 174 | 0.4194 |
| No log | 3.0 | 261 | 0.3104 |
| No log | 4.0 | 348 | 0.3037 |
| No log | 5.0 | 435 | 0.2723 |
| 0.2889 | 6.0 | 522 | 0.2368 |
| 0.2889 | 7.0 | 609 | 0.2974 |
| 0.2889 | 8.0 | 696 | 0.2923 |
| 0.2889 | 9.0 | 783 | 0.2936 |
| 0.2889 | 10.0 | 870 | 0.2952 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1