Setup
For the first experiment, I am focusing specifically on math.
I am using DeepScaleR-1.5B as a distilled model (Qwern 1.5B as base) and OpenR1-Math-220k as a dataset.
The base model for R1 distill is Qwen2.5-Math-1.5B
DeepScale is based on Qwern1.5B distillation of R1 with additional RL to make it better at math. OpenR1-Math is a set of reasoning traces sourced from full DeepSeek R1 ran on NuminaMath 1.5 dataset.
I want to test if we will see math-reasoning-specific features for the distill-and-RL model.
Here the dataset pre-processed and with a chat template applied https://huggingface.co/datasets/mitroitskii/OpenR1-Math-220k-formatted
I am using @jkminder implementation of the crosscoder - https://github.com/jkminder/dictionary_learning
Setup
For the first experiment, I am focusing specifically on math.
I am using DeepScaleR-1.5B as a distilled model (Qwern 1.5B as base) and OpenR1-Math-220k as a dataset.
The base model for R1 distill is Qwen2.5-Math-1.5B
DeepScale is based on Qwern1.5B distillation of R1 with additional RL to make it better at math. OpenR1-Math is a set of reasoning traces sourced from full DeepSeek R1 ran on NuminaMath 1.5 dataset.
I want to test if we will see math-reasoning-specific features for the distill-and-RL model.
Here the dataset pre-processed and with a chat template applied https://huggingface.co/datasets/mitroitskii/OpenR1-Math-220k-formatted
I am using @jkminder implementation of the crosscoder - https://github.com/jkminder/dictionary_learning