Duplicate from a-m-team/AM-DeepSeek-R1-0528-Distilled

Co-authored-by: TianXiaoyu <Emperorizzis@users.noreply.huggingface.co>

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README.md

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+---
+task_categories:
+- text-generation
+language:
+- en
+- zh
+tags:
+- reasoning
+size_categories:
+- 1M<n<10M
+---
+
+## 📘 Dataset Summary
+
+This dataset is a high-quality reasoning corpus **distilled from DeepSeek-R1-0528**, an improved version of the DeepSeek-R1 large language model. Compared to its initial release, DeepSeek-R1-0528 demonstrates significant advances in reasoning, instruction following, and multi-turn dialogue. Motivated by these improvements, we collected and distilled a diverse set of **2.6 million queries** across multiple domains, using DeepSeek-R1-0528 as the teacher.
+
+A notable characteristic of DeepSeek-R1-0528 is that its outputs are substantially longer than previous versions, especially in mathematics: for some math problems, the output length is **1.5 to 2 times longer** than earlier generations. This reflects more detailed, explicit step-by-step reasoning.
+
+The dataset follows a unified format and verification pipeline, enabling direct comparison with other open-source distillation corpora. It is intended to support the development of next-generation language models with strong, verifiable reasoning abilities.
+
+**Performance on this dataset training with [Qwen2.5-32B](https://huggingface.co/Qwen/Qwen2.5-32B).**
+
+| Benchmark         | [DeepSeek-R1-0528](https://huggingface.co/deepseek-ai/DeepSeek-R1-0528) | AM-DeepSeek-R1-0528-Distilled  | 
+|-------------------|--------------------------|---------------------------|
+| AIME2024          | 91.4                 | 87.1                      |
+
+## 📂 Dataset Structure
+
+### Data Fields
+
+Each sample is a dictionary with the following fields:
+
+- `system`: The system prompt used during distillation, typically guiding structured reasoning via `<think>` and `<answer>` tags.
+  - Note: Some instance's 'system' fields in our dataset are empty. The 'system' field is not used in training. Feel free to use them.
+- `conversations`: A list of dialogue turns structured as:
+  - `from`: Either `'human'` or `'assistant'`.
+  - `value`: Full message content.
+  - `info`: Metadata dictionary containing:
+    - `source`: Dataset origin (e.g., `OpenHermes-2.5`).
+    - `category`: Task domain (e.g., `math`, `code`, `general chat`).
+    - `ground_truth`: Ground truth reference (if applicable).
+    - `test_case`: Associated test case ID (optional).
+    - `instruction_constrain`: Instruction constraint metadata (optional).
+    - `think_content`: Assistant’s reasoning trace.
+    - `answer_content`: Final answer segment.
+    - `verify_score`: Verification confidence score (float ≥ 0.9).
+    - `model_name`: Name of the teacher model (`deepseek-r1-0528`).
+    - `ppl`: Perplexity of the assistant’s output.
+
+## 📈 Dataset Statistics
+
+- Shared query base: **2.6 million** unique prompts  
+- Responses distilled from **DeepSeek-R1-0528**  
+- Task Category Breakdown:
+  - **general chat**: 1,223K (47.3%)
+  - **math**: 674K (26.1%)
+  - **code**: 412K (16.0%)
+  - **science**: 220K (8.5%)
+  - **if**: 54K (2.1%)
+- Each sample is verified and filtered for output quality.
+
+![alt text](AM-distilled.png)
+
+> Note that general chat includes both multiturn and other types of data.
+
+## ✅ Verification and Quality Control
+
+All outputs underwent **automated verification**, with methods tailored to task categories:
+
+- **Math**: Math-Verify (binary pass/fail)
+- **Code**: Test-case based validation in sandbox environments
+- **Science**: Answer similarity via LLM scoring
+- **Instruction Follow**: Verified by `IFEval` validator
+- **General Chat**: Evaluated using a reward model (e.g., Decision-Tree-Reward-Llama-3.1-8B)
+
+Each dataset individually applies:
+
+- Perplexity filtering using a strong 32B LLM
+- N-gram repetition filtering
+- Structural formatting checks (e.g., presence of `<think>` and `<answer>`)
+
+## ⚠️ Limitations
+
+Developers should strictly limit the use of this project’s open-sourced code, data, models, and related artifacts to **research purposes only**. **Commercial use and any applications that could potentially cause harm are strictly prohibited**.
+
+The content in this dataset does not reflect the views, beliefs, or endorsements of any individual or institution. The authors disclaim any responsibility for consequences arising from the use, misuse, or interpretation of the dataset and associated materials.
+
+## 📜 Citation
+
+If you use this dataset, please cite:
+
+```
+@misc{AM-DeepSeek-R1-0528-Distilled,
+    title  = {AM-DeepSeek-R1-0528-Distilled},
+    url    = {https://github.com/a-m-team/a-m-models},
+    author = {a-m-team},
+    month  = {June},
+    year   = {2025}
+}
+```
+

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