---
library_name: transformers
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: 0.1713
- F1: 0.9670
- Roc Auc: 0.9670
- Accuracy: 0.9670

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 63   | 0.1713          | 0.9670 | 0.9670  | 0.9670   |
| 0.1703        | 2.0   | 126  | 0.1866          | 0.9670 | 0.9670  | 0.9670   |
| 0.1703        | 3.0   | 189  | 0.1876          | 0.9670 | 0.9670  | 0.9670   |
| 0.0284        | 4.0   | 252  | 0.1917          | 0.9670 | 0.9670  | 0.9670   |
| 0.0283        | 5.0   | 315  | 0.1924          | 0.9670 | 0.9670  | 0.9670   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0