---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-0.5B-Instruct
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Qwen2-0.5B-Reward
  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. -->

# Qwen2-0.5B-Reward

This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co./Qwen/Qwen2-0.5B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5182
- Accuracy: 0.728

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6444        | 0.0516 | 50   | 0.6037          | 0.672    |
| 0.5825        | 0.1032 | 100  | 0.5859          | 0.682    |
| 0.5732        | 0.1548 | 150  | 0.5751          | 0.704    |
| 0.5494        | 0.2064 | 200  | 0.5514          | 0.701    |
| 0.5654        | 0.2580 | 250  | 0.5427          | 0.709    |
| 0.5514        | 0.3096 | 300  | 0.5309          | 0.723    |
| 0.537         | 0.3612 | 350  | 0.5259          | 0.735    |
| 0.5236        | 0.4128 | 400  | 0.5368          | 0.714    |
| 0.536         | 0.4644 | 450  | 0.5451          | 0.726    |
| 0.5236        | 0.5160 | 500  | 0.5371          | 0.727    |
| 0.526         | 0.5676 | 550  | 0.5293          | 0.729    |
| 0.5197        | 0.6192 | 600  | 0.5239          | 0.727    |
| 0.525         | 0.6708 | 650  | 0.5227          | 0.732    |
| 0.5123        | 0.7224 | 700  | 0.5206          | 0.723    |
| 0.5171        | 0.7740 | 750  | 0.5237          | 0.718    |
| 0.5156        | 0.8256 | 800  | 0.5245          | 0.722    |
| 0.5115        | 0.8772 | 850  | 0.5234          | 0.723    |
| 0.5007        | 0.9288 | 900  | 0.5207          | 0.729    |
| 0.5018        | 0.9804 | 950  | 0.5182          | 0.728    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1