bert-large-uncased-whole-word-masking-finetuned-policy-named-insured
This model is a fine-tuned version of bert-large-uncased-whole-word-masking-finetuned-squad on the policies-named-insured dataset. It achieves the following results on the evaluation set:
- Loss: 0.0264
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 478 | 0.0402 |
| 0.0557 | 2.0 | 956 | 0.0326 |
| 0.0106 | 3.0 | 1434 | 0.0264 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2