---
library_name: peft
license: other
base_model: Qwen/Qwen2.5-14B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: MATH_training_response_Qwen2.5-32B-Instruct
  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_response_Qwen2.5-32B-Instruct

This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) on the MATH_training_Qwen2.5-32B-Instruct dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0680

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.093         | 0.1500 | 200  | 0.0782          |
| 0.0361        | 0.3001 | 400  | 0.0700          |
| 0.0649        | 0.4501 | 600  | 0.0710          |
| 0.0468        | 0.6002 | 800  | 0.0700          |
| 0.1057        | 0.7502 | 1000 | 0.0689          |
| 0.0632        | 0.9002 | 1200 | 0.0670          |
| 0.0446        | 1.0503 | 1400 | 0.0680          |
| 0.0486        | 1.2003 | 1600 | 0.0680          |
| 0.0481        | 1.3503 | 1800 | 0.0675          |
| 0.045         | 1.5004 | 2000 | 0.0689          |
| 0.0471        | 1.6504 | 2200 | 0.0682          |
| 0.0317        | 1.8005 | 2400 | 0.0683          |
| 0.0489        | 1.9505 | 2600 | 0.0682          |


### Framework versions

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