RuletakerBert
This model is a fine-tuned version of bert-base-cased on the Ruletaker dataset. It achieves the following results on the evaluation set:
- Loss: 0.1587
- Accuracy: 0.9312
Model description
This model is to verify the entailment relationship between two sentence
Intended uses & limitations
We use it for multple purpose, including RLLF
Training and evaluation data
Ruletaker dataset
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1672 | 1.0 | 10004 | 0.1587 | 0.9312 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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