---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-Math-7B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: GenPRM-78k-train-5:5-decontamination
  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. -->

# GenPRM-78k-train-5:5-decontamination

This model is a fine-tuned version of [/data1/model/Qwen2.5-Math-7B-Instruct](https://huggingface.co//data1/model/Qwen2.5-Math-7B-Instruct) on the GenPRM-78k-train-5:5-decontamination dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2910

## 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3951        | 0.0823 | 100  | 0.3771          |
| 0.3471        | 0.1647 | 200  | 0.3431          |
| 0.3295        | 0.2470 | 300  | 0.3266          |
| 0.3162        | 0.3294 | 400  | 0.3161          |
| 0.3143        | 0.4117 | 500  | 0.3084          |
| 0.3054        | 0.4940 | 600  | 0.3029          |
| 0.3031        | 0.5764 | 700  | 0.2985          |
| 0.2988        | 0.6587 | 800  | 0.2953          |
| 0.2965        | 0.7410 | 900  | 0.2932          |
| 0.2935        | 0.8234 | 1000 | 0.2918          |
| 0.2975        | 0.9057 | 1100 | 0.2911          |
| 0.304         | 0.9881 | 1200 | 0.2910          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1