Update README.md

README.md

@@ -14,6 +14,9 @@ license: apache-2.0
 
 This is a finetune of [Qwen2.5-Math-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-7B-Instruct) on [OpenR1-220k-Math](https://huggingface.co/datasets/open-r1/openr1-220k-math) (`default` split).
 
+> [!NOTE]
+> Check out [OpenR1-Distill-7B](https://huggingface.co/open-r1/OpenR1-Distill-7B) for an improved model that was trained on [open-r1/Mixture-of-Thoughts](https://huggingface.co/datasets/open-r1/Mixture-of-Thoughts) and replicates the performance of [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) across multiple reasoning domains.
+
 ## Quick start
 
 ```python
@@ -39,12 +42,12 @@ messages = [
 
 ## Training 
 
-We train the model on the `default` split of [OpenR1-220k-Math](https://huggingface.co/datasets/open-r1/openr1-220k-math) for 3 epochs. We use learning rate of 5e-5 and extend the context length from 4k to 32k, by increasing RoPE frequency to 300k. The training follows a linear learning rate schedule with a 10% warmup phase. The table below compares the performance of OpenR1-Qwen-7B to DeepSeek-Distill-Qwen-7B and OpenThinker-7B using [lighteval](https://github.com/huggingface/open-r1/tree/main?tab=readme-ov-file#evaluating-models).
+We train the model on the `default` split of [OpenR1-220k-Math](https://huggingface.co/datasets/open-r1/openr1-220k-math) for 3 epochs. We use learning rate of 5e-5 and extend the context length from 4k to 32k, by increasing RoPE frequency to 300k. The training follows a linear learning rate schedule with a 10% warmup phase. The table below compares the performance of OpenR1-Qwen-7B to [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) and [OpenThinker-7B](https://huggingface.co/open-thoughts/OpenThinker-7B) using [lighteval](https://github.com/huggingface/open-r1/tree/main?tab=readme-ov-file#evaluating-models).
 
 You can find the training and evaluation code at: https://github.com/huggingface/open-r1/
 
-| Model | MATH-500 | AIME24 |  AIME25 |
-| --- | --- | --- |--- |
-| DeepSeek-Distill-Qwen-7B | 91.6 | 43.3 | 40.0|
-| OpenR1-Qwen-7B | 90.6 | 36.7 | 40.0 |
-| OpenThinker-7B | 89.6 | 30.0 | 33.3 |
+| Model                    | MATH-500 | AIME 2024 | AIME 2025 | GPQA-D |
+|--------------------------|----------|-----------|-----------|--------|
+| DeepSeek-Distill-Qwen-7B | 93.5     | 51.3      | 35.8      | 52.4   |
+| OpenR1-Qwen-7B           | 90.6     | 47.0      | 33.2      | 42.4   |
+| OpenThinker-7B           | 86.4     | 31.3      | 24.6      | 39.1   |