BERT_BOOLQ_Circa_YN
This model is a fine-tuned version of lewtun/bert-large-uncased-wwm-finetuned-boolq on the circa dataset. It achieves the following results on the evaluation set:
- Loss: 0.3944
- Accuracy: 0.9091
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: 32
- eval_batch_size: 32
- 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 | Accuracy |
|---|---|---|---|---|
| 0.5055 | 1.0 | 619 | 0.3336 | 0.8868 |
| 0.2832 | 2.0 | 1238 | 0.3039 | 0.9100 |
| 0.1729 | 3.0 | 1857 | 0.3944 | 0.9091 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2