---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: RewardModelOnlyOnAnswer
  results: []
---

<!-- 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. -->

# RewardModelOnlyOnAnswer

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6051
- F1: 0.5377
- Roc Auc: 0.6538
- Accuracy: 0.53

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 258  | 0.6315          | 0.0    | 0.5     | 0.0      |
| 0.6039        | 2.0   | 516  | 0.6412          | 0.3732 | 0.5613  | 0.32     |
| 0.6039        | 3.0   | 774  | 0.6051          | 0.5377 | 0.6538  | 0.53     |
| 0.3801        | 4.0   | 1032 | 0.7261          | 0.5163 | 0.6375  | 0.51     |
| 0.3801        | 5.0   | 1290 | 0.8381          | 0.4792 | 0.6062  | 0.46     |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3