---
base_model: Qwen/Qwen2.5-1.5B-Instruct
datasets: gsm8k-dataset
library_name: transformers
model_name: Qwen2.5-1.5B-Instruct_math_grpo_cosine_0.5_0.5_SEC0.3DRO1.0G0.0_minpTrue_1600
tags:
- generated_from_trainer
- trl
- grpo
licence: license
---

# Model Card for Qwen2.5-1.5B-Instruct_math_grpo_cosine_0.5_0.5_SEC0.3DRO1.0G0.0_minpTrue_1600

This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the [gsm8k-dataset](https://huggingface.co/datasets/gsm8k-dataset) dataset.
It has been trained using [E2H](https://github.com/divelab/E2H-Reasoning) on the top of [TRL](https://github.com/huggingface/trl).

## Quick start

```python
from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="shubhamprshr/Qwen2.5-1.5B-Instruct_math_grpo_cosine_0.5_0.5_SEC0.3DRO1.0G0.0_minpTrue_1600", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```

## Training procedure

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/shubhamprshr27-tamu/dapo_e2h/runs/upy1drqf) 


This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).

### Framework versions

- TRL: 0.19.1
- Transformers: 4.53.1
- Pytorch: 2.7.0
- Datasets: 3.6.0
- Tokenizers: 0.21.4

## Citations

Cite E2H as:

```bibtex
@inproceedings{parashar2026curriculum,
  title     = {Curriculum Reinforcement Learning from Easy to Hard Tasks Improves {LLM} Reasoning},
  author    = {Parashar, Shubham and Gui, Shurui and Li, Xiner and Ling, Hongyi and Vemuri, Sushil and Olson, Blake and Li, Eric and Zhang, Yu and Caverlee, James and Kalathil, Dileep and Ji, Shuiwang},
  booktitle = {The Fourteenth International Conference on Learning Representations},
  year      = {2026},
  url       = {https://openreview.net/forum?id=KJvHnl3kUv}
}
```