---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: RewardModel_RobertaBase
  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. -->

# RewardModel_RobertaBase

This model is a fine-tuned version of [roberta-base](https://huggingface.co./roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5050
- F1: 0.7522
- Roc Auc: 0.7526
- Accuracy: 0.7509

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.6464        | 1.0   | 100  | 0.6186          | 0.6772 | 0.6772  | 0.6737   |
| 0.5776        | 2.0   | 200  | 0.5439          | 0.7298 | 0.7298  | 0.7298   |
| 0.4806        | 3.0   | 300  | 0.5050          | 0.7522 | 0.7526  | 0.7509   |
| 0.3909        | 4.0   | 400  | 0.8594          | 0.6690 | 0.6684  | 0.6667   |
| 0.331         | 5.0   | 500  | 0.7766          | 0.7206 | 0.7211  | 0.7193   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1