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---
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
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