---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-14B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: prm_cot
  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. -->

# prm_cot

This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) on the sky_math_step_level_gen_prm_cot dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3308

## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.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: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3221        | 0.2539 | 500  | 0.3276          |
| 0.3095        | 0.5079 | 1000 | 0.3185          |
| 0.308         | 0.7618 | 1500 | 0.3138          |
| 0.2496        | 1.0157 | 2000 | 0.3163          |
| 0.248         | 1.2697 | 2500 | 0.3150          |
| 0.2526        | 1.5236 | 3000 | 0.3125          |
| 0.254         | 1.7776 | 3500 | 0.3094          |
| 0.1867        | 2.0315 | 4000 | 0.3303          |
| 0.1863        | 2.2854 | 4500 | 0.3317          |
| 0.1825        | 2.5394 | 5000 | 0.3310          |
| 0.1787        | 2.7933 | 5500 | 0.3310          |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1