Update README.md

README.md

@@ -14,6 +14,10 @@ library_name: transformers
 
 ## FastCuRL Overview
 
+### 2025-05-23
+
+We release **FastCuRL-1.5B-V3** and **FastCuRL-1.5B-V2**.
+
 ### 2025-03-17
 
 We release **FastCuRL-1.5B-Preview**, a slow-thinking reasoning model that **outperforms** the previous SoTA *DeepScaleR-1.5B-Preview* with **50% training steps**! We adapt a novel curriculum-guided iterative lengthening reinforcement learning to the *DeepSeek-R1-Distill-Qwen-1.5B* and observe continuous performance improvement as training steps increase. To better reproduce our work and advance research progress, we open-source our code, model, and data.
@@ -37,7 +41,9 @@ We report Pass@1 accuracy averaged over 16 samples for each problem.
 | DeepSeek-R1-Distill-Qwen-1.5B | 28.8 | 82.8 | 62.9 | 26.5 | 43.3 | 48.9 |
 | Still-1.5B | 32.5 | 84.4 | 66.7 | 29.0 | 45.4 | 51.6 |
 | DeepScaleR-1.5B-Preview | 43.1 | 87.8 | 73.6 | 30.2 | 50.0 | 57.0 |
-| <strong>FastCuRL-1.5B-Preview</strong> | <strong>43.1</strong> | <strong>88.0</strong> | <strong>74.2</strong> | 31.6 | <strong>50.4</strong> | <strong>57.5</strong> |
+| <strong>FastCuRL-1.5B-Preview</strong> | 43.1 | 88.0 | 74.2 | 31.6 | 50.4 | 57.5 |
+| <strong>FastCuRL-1.5B-V2</strong> | 47.5 | 89.3 | 77.0 | 32.8 | 53.3 | 60.0 |
+| <strong>FastCuRL-1.5B-V3</strong> | <strong>49.6</strong> | <strong>90.5</strong> | <strong>78.5</strong> | <strong>34.7</strong> | <strong>54.5</strong> | <strong>61.6</strong> |
 
 ## Training Data
 Following DeepScaleR, our training dataset consists of 40,315 unique problem-answer pairs compiled from: