---
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: 0.5009
- F1: 0.7738
- Roc Auc: 0.7738
- Accuracy: 0.7698

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 93   | 0.5440          | 0.7331 | 0.7341  | 0.7302   |
| 0.648         | 2.0   | 186  | 0.5009          | 0.7738 | 0.7738  | 0.7698   |
| 0.5515        | 3.0   | 279  | 0.4938          | 0.7545 | 0.7560  | 0.75     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1