---
library_name: transformers
license: apache-2.0
base_model: distilroberta-base
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: reward_model
  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. -->

# reward_model

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5988
- Accuracy: 0.65

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7043        | 0.0150 | 20   | 0.6886          | 0.54     |
| 0.6671        | 0.0301 | 40   | 0.6924          | 0.53     |
| 0.6131        | 0.0451 | 60   | 0.7038          | 0.58     |
| 0.6149        | 0.0602 | 80   | 0.6759          | 0.6      |
| 0.6539        | 0.0752 | 100  | 0.6593          | 0.58     |
| 0.6671        | 0.0902 | 120  | 0.7227          | 0.59     |
| 0.6863        | 0.1053 | 140  | 0.6452          | 0.58     |
| 0.6332        | 0.1203 | 160  | 0.6394          | 0.64     |
| 0.6259        | 0.1353 | 180  | 0.6630          | 0.61     |
| 0.6257        | 0.1504 | 200  | 0.6369          | 0.61     |
| 0.5376        | 0.1654 | 220  | 0.6460          | 0.62     |
| 0.6734        | 0.1805 | 240  | 0.6404          | 0.62     |
| 0.724         | 0.1955 | 260  | 0.7469          | 0.6      |
| 0.541         | 0.2105 | 280  | 0.6295          | 0.64     |
| 0.5495        | 0.2256 | 300  | 0.6182          | 0.65     |
| 0.7581        | 0.2406 | 320  | 0.6262          | 0.6      |
| 0.5234        | 0.2556 | 340  | 0.6228          | 0.63     |
| 0.5787        | 0.2707 | 360  | 0.6208          | 0.64     |
| 0.6025        | 0.2857 | 380  | 0.6069          | 0.65     |
| 0.6061        | 0.3008 | 400  | 0.6166          | 0.65     |
| 0.8482        | 0.3158 | 420  | 0.6078          | 0.65     |
| 0.5613        | 0.3308 | 440  | 0.5940          | 0.65     |
| 0.7284        | 0.3459 | 460  | 0.6042          | 0.65     |
| 0.5778        | 0.3609 | 480  | 0.5990          | 0.65     |
| 0.6848        | 0.3759 | 500  | 0.5988          | 0.65     |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3