71 lines
2.4 KiB
Markdown
71 lines
2.4 KiB
Markdown
---
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license: apache-2.0
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base_model: Qwen/Qwen3-4B-Thinking-2507
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tags:
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- aster
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- reinforcement-learning
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- sft
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- reproduction
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metrics:
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- accuracy
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model-index:
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- name: ASTER_4B
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AIME 2025
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type: aime2025
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metrics:
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- name: Accuracy
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type: accuracy
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value: 87.7
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HMMT 2025 Feb
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type: hmmt_2025_feb
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metrics:
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- name: Accuracy
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type: accuracy
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value: 77.1
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---
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# ASTER_4B (Independent Reproduction)
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[](https://arxiv.org/pdf/2602.01204)
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[](https://github.com/Rainyrou/ASTER)
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[](https://huggingface.co/datasets/choosealicense/licenses/apache-2.0)
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## Model Description
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**ASTER_4B** is an independent reproduction of the ASTER framework. This model is fine-tuned based on [Qwen/Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507), strictly adhering to the experimental details and hyperparameter settings described in the original ASTER paper.
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> ⚠️ **Note:** This is a **reproduction project**. We aim to verify the effectiveness of the ASTER method by strictly following the official paper's details.
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## Training Data (SFT)
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The model was trained using our reproduced dataset: **Aster_SFT4K**.
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This dataset serves as a tiny yet effective SFT set, constructed to replicate the exact data distribution and formatting used in the original ASTER experiments. You can find the dataset details here:
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* **Dataset Repo:** [ASTER_SFT4K](https://huggingface.co/datasets/QuantumStackOverflow/ASTER_SFT4K)
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## Evaluation Results
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We evaluated the model's performance on challenging mathematical benchmarks. The evaluation was conducted under the **exact generation configuration** specified in the ASTER paper to ensure fair comparison.
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**Generation Config:**
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* **Temperature:** `1.0`
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* **Top_p:** `1.0`
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* **Max_context_length**: `96256`
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| Benchmark | Score (%) |
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| :--- | :--- |
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| **AIME 2025** | **87.7** |
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| **HMMT 2025 (Feb)** | **77.1** |
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