---
base_model: Qwen/Qwen2-0.5B-Instruct
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- trl
- reward-trainer
- generated_from_trainer
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: 0.6423
- Accuracy: 0.628

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.9852        | 0.0516 | 50   | 0.9181          | 0.478    |
| 0.811         | 0.1032 | 100  | 0.8217          | 0.52     |
| 0.7701        | 0.1548 | 150  | 0.7529          | 0.56     |
| 0.7239        | 0.2064 | 200  | 0.7145          | 0.59     |
| 0.723         | 0.2580 | 250  | 0.6917          | 0.597    |
| 0.6912        | 0.3096 | 300  | 0.6812          | 0.615    |
| 0.6577        | 0.3612 | 350  | 0.6702          | 0.626    |
| 0.645         | 0.4128 | 400  | 0.6632          | 0.616    |
| 0.6749        | 0.4644 | 450  | 0.6584          | 0.623    |
| 0.6497        | 0.5160 | 500  | 0.6541          | 0.625    |
| 0.659         | 0.5676 | 550  | 0.6526          | 0.626    |
| 0.634         | 0.6192 | 600  | 0.6495          | 0.626    |
| 0.6393        | 0.6708 | 650  | 0.6463          | 0.624    |
| 0.6263        | 0.7224 | 700  | 0.6456          | 0.629    |
| 0.6428        | 0.7740 | 750  | 0.6440          | 0.625    |
| 0.6335        | 0.8256 | 800  | 0.6431          | 0.634    |
| 0.6313        | 0.8772 | 850  | 0.6425          | 0.638    |
| 0.6323        | 0.9288 | 900  | 0.6419          | 0.636    |
| 0.6313        | 0.9804 | 950  | 0.6424          | 0.645    |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1