Update README.md

README.md

@@ -10,33 +10,28 @@ pipeline_tag: text-generation
 # Model Card
 
 ## 1. Model Details
-This model is the fine-tuned checkpoint described in the paper **"Not All Steps are Informative: On the Linearity of LLMs’ RLVR Training"**. It was trained using Reinforcement Learning (GRPO) to enhance mathematical reasoning capabilities.
+This model is the fine-tuned checkpoint described in the paper **"Not All Steps are Informative: On the Linearity of LLMs’ RLVR Training"**. It was trained using Reinforcement Learning (RL) to enhance reasoning capabilities.
 
 - **Paper:** [ArXiv](https://arxiv.org/pdf/2601.04537v1)
 - **Code:** [Github](https://github.com/Miaow-Lab/RLVR-Linearity)
 - **Base Model:** [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B)
 - **Training Method:** GRPO
 
-## 2. Performance
-We evaluated the model on standard math benchmarks. Key results include:
 
-| Benchmark | Avg@64 |
-| :--- | :--- |
-| AIME 2024 | **41.93%** |
-
-
-## 3. Training Details
+## 2. Training Details
 
 - **Hyperparameters:**
   - Learning Rate: `1e-6`
   - Train Batch Size: `128`
   - PPO Mini Batch Size: `64`
   - RL Algorithm: `GRPO`
+  - Rollout Temperature: 1.0
+  - Group Size: 16
 - **Compute:** Trained on `32 x H100` GPUs for about `150` hours.
 
 For full training configurations, please refer to the `config.json` or the training scripts in our [GitHub](https://github.com/Miaow-Lab/RLVR-Linearity).
 
-## 4. Citation
+## 3. Citation
 
 If you use this model in your research, please cite our paper:
 
@@ -50,4 +45,8 @@ If you use this model in your research, please cite our paper:
       primaryClass={cs.LG},
       url={https://arxiv.org/abs/2601.04537}, 
 }
-```
+```
+
+> [!TIP]
+> **Motivation for this Model**
+> This checkpoint is released primarily as a research artifact to facilitate the analysis of linearity in model outputs and weight updates during RLVR fine‑tuning.