--- base_model: Qwen/Qwen3-0.6B-Base datasets: open-r1/Mixture-of-Thoughts library_name: transformers model_name: R1-Distill-0.6B tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for R1-Distill-0.6B-Qwen This model is a fine-tuned version of [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) on the [open-r1/Mixture-of-Thoughts](https://huggingface.co/datasets/open-r1/Mixture-of-Thoughts) dataset. It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="alphadl/R1-Distill-0.6B", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure This model was trained with SFT. ### Framework versions - TRL: 0.18.0 - Transformers: 4.52.3 - Pytorch: 2.6.0 - Datasets: 3.2.0 - Tokenizers: 0.21.1 ### Evaluation - lighteval: 0.10.0 | Model | Qwen3-0.6B-Base | R1-Distill-0.6B (Ours) | |:-------------|:---------------:|:----------------------:| | Math-500 | 38.2 | 41.0(`+2.8`) | | GPQA Diamond | 24.2 | 28.3(`+4.1`) | ```shell export VLLM_WORKER_MULTIPROC_METHOD=spawn # Required for vLLM export NUMEXPR_MAX_THREADS=128 # Utilize all 128 cores for numerical computations MODEL=data/R1-Distill-0.6B # Evaluate the base model # MODEL=Qwen/Qwen3-0.6B-Base MODEL_ARGS="model_name=$MODEL,dtype=bfloat16,max_model_length=32768,gpu_memory_utilization=0.8,generation_parameters={max_new_tokens:8192,temperature:0.6,top_p:0.95}" OUTPUT_DIR=data/evals/$MODEL # Math 500 TASK=math_500 lighteval vllm $MODEL_ARGS "lighteval|$TASK|0|0" \ --use-chat-template \ --output-dir $OUTPUT_DIR # GPQA Diamond TASK=gpqa:diamond lighteval vllm $MODEL_ARGS "lighteval|$TASK|0|0" \ --use-chat-template \ --output-dir $OUTPUT_DIR ```