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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: 0.5212
- Accuracy: 0.731
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6316 | 0.0516 | 50 | 0.5943 | 0.666 |
| 0.573 | 0.1032 | 100 | 0.5857 | 0.698 |
| 0.5809 | 0.1548 | 150 | 0.5718 | 0.705 |
| 0.5493 | 0.2064 | 200 | 0.5450 | 0.714 |
| 0.5649 | 0.2580 | 250 | 0.5483 | 0.713 |
| 0.5585 | 0.3096 | 300 | 0.5265 | 0.734 |
| 0.5431 | 0.3612 | 350 | 0.5295 | 0.732 |
| 0.5209 | 0.4128 | 400 | 0.5334 | 0.735 |
| 0.5414 | 0.4644 | 450 | 0.5409 | 0.726 |
| 0.525 | 0.5160 | 500 | 0.5387 | 0.731 |
| 0.5242 | 0.5676 | 550 | 0.5255 | 0.727 |
| 0.521 | 0.6192 | 600 | 0.5208 | 0.727 |
| 0.5227 | 0.6708 | 650 | 0.5191 | 0.736 |
| 0.5132 | 0.7224 | 700 | 0.5186 | 0.728 |
| 0.5145 | 0.7740 | 750 | 0.5236 | 0.729 |
| 0.514 | 0.8256 | 800 | 0.5249 | 0.728 |
| 0.5087 | 0.8772 | 850 | 0.5261 | 0.725 |
| 0.5009 | 0.9288 | 900 | 0.5229 | 0.727 |
| 0.4989 | 0.9804 | 950 | 0.5213 | 0.731 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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