---
library_name: peft
license: other
base_model: Qwen/Qwen2.5-32B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: MATH_training_QwQ_32B_Preview
  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. -->

# MATH_training_QwQ_32B_Preview

This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) on the MATH_training_Qwen_QwQ_32B_Preview dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1193

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.2322        | 0.1564 | 200  | 0.2143          |
| 0.1419        | 0.3127 | 400  | 0.1674          |
| 0.1137        | 0.4691 | 600  | 0.1510          |
| 0.1457        | 0.6255 | 800  | 0.1406          |
| 0.0953        | 0.7819 | 1000 | 0.1333          |
| 0.1201        | 0.9382 | 1200 | 0.1268          |
| 0.0899        | 1.0946 | 1400 | 0.1289          |
| 0.0548        | 1.2510 | 1600 | 0.1269          |
| 0.0323        | 1.4073 | 1800 | 0.1240          |
| 0.0414        | 1.5637 | 2000 | 0.1207          |
| 0.0375        | 1.7201 | 2200 | 0.1202          |
| 0.0512        | 1.8765 | 2400 | 0.1201          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3