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II-Thought-1.5B-Preview

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Phu Nguyen commited on Mar 24, 2025

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----
-library_name: transformers
-tags: []
----
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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+# II-Thought-1.5B-Preview
+## Overview
+**II-Thought-1.5B-Preview** is a Reinforcement Learning enhanced language model trained on **a subset of [II-Thought-RL-v0](https://huggingface.co/datasets/Intelligent-Internet/II-Thought-RL-v0)**, the first large-scale, multi-task dataset designed for RL. While II-Thought-RL-v0 spans multiple domains (mathematics, coding, medicine, science, etc.), this preview release was trained on randomly sampled **50K math subset** ([dataset link](https://huggingface.co/datasets/Intelligent-Internet/II-Thought-RL-v0-Math-50K)).
+## Training Methodology
+- **Framework**: [ii_thought](https://github.com/Intelligent-Internet/ii-thought) / [verl](https://github.com/volcengine/verl)
+- **Algorithm**: GRPO
+- **Reward Modeling**
+  - **Answer correctness reward**
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/67c563afa34e1ad5a3533ccf/X15GjihIRO9hkfL361Pfd.png" width="500">
+  - **Format correctness reward**
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/67c563afa34e1ad5a3533ccf/ib5bJu4lMkREigExRAUn9.png" width="500">
+  - **Final reward function**
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/67c563afa34e1ad5a3533ccf/UXsKqJIFjCpT_vUUSTigr.png" width="500">
+For a deeper look into the implementation details, refer to the our repository: [Intelligent-Internet/ii-thought](https://github.com/Intelligent-Internet/ii-thought/tree/main).
+## Evaluation Results
+We used the [EvalScope](https://github.com/modelscope/evalscope) to evaluate models and report Pass@1 accuracy across all benchmarks. The number of responses generated per problem is as follows:
+  - 64 responses: `AMC23, AIME24, AIME25, Vietnamese-Entrance-Math-Exam`
+  - 8 responses: `Minerva-Math, Math-Gakao-2023-English`
+  - 4 responses: `Math500, Olympiad-Bench`
+  - 1 responses: `IFEval`
+Sampling Configs:
+  - Max context length: 16384
+  - Temperature: 0.6
+  - Top p: 0.95
+  - Top k: 40
+  - seed: 42
+| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | II-Thought-1.5B-Preview |
+|-----------|-------------------------------|--------------------------|
+| AMC23 | 68.48 | **79.41** |
+| AIME24 | 28.07 | **33.39** |
+| AIME25 | 22.6 | **25.68** |
+| Olympiad Bench | 42.04 | **51.63** |
+| Math500 | 82.3 | **86.8** |
+| Math Gakao 2023 English | 72.18 | **76.85** |
+| Minerva Math | 27.62 | **31.89** |
+| Vietnamese Entrance Math Exam | 39.85 | **45.12** |
+| LiveCodeBench | 16.66 | **19.84** |
+| IFEval | 41.95 | **45.56** |
+| **Average** | 44.175 | **49.61** |
+## How To Use
+Our model can be utilized in the same manner as Qwen or Deepseek-R1-Distill models.
+For instance, you can easily start a service using [vLLM](https://github.com/vllm-project/vllm):
+```bash
+vllm serve Intelligent-Internet/II-Thought-1.5B-Preview
+```
+You can also easily start a service using [SGLang](https://github.com/sgl-project/sglang)
+```bash
+python -m sglang.launch_server --model Intelligent-Internet/II-Thought-1.5B-Preview
+```
+### Usage Guidelines
+- Recommended Sampling Parameters: temperature = 0.6, top_p = 0.95
+- For mathematical problems, explicitly request step-by-step reasoning and format the final answer within `\\boxed{}` (e.g., *"Please reason step by step, and put your final answer within \\boxed{}."*).
+## Citation
+```bib
+@misc{2025iithought,
+      title={II-Thought : A Large-Scale, High-Quality Reasoning Dataset},
+      author={Intelligent Internet}
+      year={2025},
+}
+```