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Reinforcement Learning from Verifiable Rewards

In this project, I finetune Qwen3-1.7B model using the Group Relative Policy Optimization (GRPO) algorithm. I also use LORA for finetuning. The dataset was taken from dataset

Both the installation and training are done in one script.

Training

bash train.sh

After training, we merge the weights of the LORA adapter with the base model.

Merging

python3 post_train_merge.py

Now, we can evaluate the model on the test set.

Evaluation

bash eval.sh

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