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Qwen2.5-7B-SFT

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qwen2

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----
-library_name: transformers
-tags: []
----
-# Model Card for Model ID
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-## Model Details
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+# Online-DPO-R1
+* **Blog**: https://www.notion.so/Online-DPO-R1-1908b9a70e7b80c3bc83f4cf04b2f175
+* **Authors**:
+* **Code**: https://github.com/RLHFlow/Online-DPO-R1
+## Introduction
+We release unofficial checkpoints for PPO, iterative DPO and rejection sampling (RAFT) trained from Qwen2.5-MATH-7B-base with rule-based RL, which are based on the success of Deepseek-R1-Zero and recent replications of PPO approach.
+Evaluated on five widely-adopted benchmarks **AIME 2024**, **MATH 500**, **AMC**, **Minerva Math**, **OlympiadBench**, our **iterative DPO** and **RAFT** model achieve
+significant enhancement compared to the base model and are comparable to the PPO approach.
+Our models are trained by using the prompt set from the MATH training set and Numina Math.
+Moreover, we provide a [detailed recipe](https://github.com/RLHFlow/Online-DPO-R1) to reproduce the model. Enjoy!
+## Model Releases
+- [PPO model] (https://huggingface.co/RLHFlow/Qwen2.5-7B-PPO-Zero)
+- [Iterative DPO] (https://huggingface.co/RLHFlow/Qwen2.5-7B-DPO-Zero)
+- [Iterative DPO with Negative Log-Likelihood (NLL)] (https://huggingface.co/RLHFlow/Qwen2.5-7B-DPO-NLL-Zero)
+- [Raft] (https://huggingface.co/RLHFlow/Qwen2.5-7B-RAFT-Zero)
+## Dataset
+## Training methods
+- We first SFT the base model on the the MATH training set [RLHFlow/qwq_gen_sft_15k](https://huggingface.co/datasets/RLHFlow/qwq_gen_sft_15k).
+More detailed can be found in our [blog](https://www.notion.so/Online-DPO-R1-1908b9a70e7b80c3bc83f4cf04b2f175)!
+## Performance
+| **Model**                  | **AIME 2024** | **MATH 500** | **AMC** | **Minerva Math** | **OlympiadBench** | **Average** |
+|----------------------------|---------------|--------------|---------|------------------|-------------------|-------------|
+| **Ours**                   |            |           |            |          |               |              |
+| RLHFlow/Qwen2.5-7B-PPO-Zero        | **43.3 (+26.6)**   | 79.4 (+27.0)      | **62.5 (+10.0)**      | 33.1   (+20.2)      | 40.7   (+24.3)     | **51.8 (+21.6)** |
+| RLHFlow/Qwen2.5-7B-DPO-Zero        | 26.7 (+10.0)       | 76.8 (+24.4)      | **62.5 (+10.0)**      | 30.9 (+18.0)        | 37.9 (+21.5)       | 47.0 (+16.8)     |
+| RLHFlow/Qwen2.5-7B-DPO             | 30.0 (+13.3)       | **84.4 (+32.0)**  | **62.5 (+10.0)**      | **33.5 (+20.6)**    | **48.4 (+32.0)**   | **51.8 (+21.6)** |
+| RLHFlow/Qwen2.5-7B-RAFT-Zero       | 20.0 (+3.3)        | 77.6 (+25.2)      | 55.0 (+2.5)           | 30.5   (+17.6)      | 38.7   (+22.3)     | 44.4   (+14.2)   |
+| **Baselines**             |            |           |            |          |               |              |
+| Qwen2.5-Math-7B-Base       | 16.7       | 52.4      | 52.5       | 12.9     | 16.4          | 30.2         |
+| Qwen2.5-Math-7B-Base + SFT Warm-up | 20.0       | 73.2      | 62.5       | 30.5     | 35.6          | 44.4         |
+| Qwen-2.5-Math-7B-Instruct  | 13.3       | 79.8      | 50.6       | 34.6     | 40.7          | 43.8         |
+| Llama-3.1-70B-Instruct     | 16.7       | 64.6      | 30.1       | 35.3     | 31.9          | 35.7         |
+| Eurus-2-7B-PRIME           | 26.7       | 79.2      | 57.8       | 38.6     | 42.1          | 48.9         |
+| GPT-4o                     | 9.3        | 76.4      | 45.8       | 36.8     | 43.3          | 43.3         |
+## Usage
+## Citation