---
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: 0.1047
- F1: 0.9722
- Roc Auc: 0.9792
- Accuracy: 0.9722

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 15   | 0.6256          | 0.0    | 0.5     | 0.0      |
| No log        | 2.0   | 30   | 0.5210          | 0.3448 | 0.6042  | 0.2083   |
| No log        | 3.0   | 45   | 0.3479          | 0.8143 | 0.8576  | 0.7639   |
| No log        | 4.0   | 60   | 0.2431          | 0.9241 | 0.9444  | 0.9167   |
| No log        | 5.0   | 75   | 0.1917          | 0.9315 | 0.9514  | 0.9167   |
| No log        | 6.0   | 90   | 0.1364          | 0.9655 | 0.9757  | 0.9583   |
| 0.3628        | 7.0   | 105  | 0.1120          | 0.9583 | 0.9688  | 0.9583   |
| 0.3628        | 8.0   | 120  | 0.0967          | 0.9655 | 0.9757  | 0.9583   |
| 0.3628        | 9.0   | 135  | 0.1047          | 0.9722 | 0.9792  | 0.9722   |
| 0.3628        | 10.0  | 150  | 0.0928          | 0.9722 | 0.9792  | 0.9722   |


### Framework versions

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