
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# RuletakerBert

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-cased", "model-index": [{"name": "RuletakerBert", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us