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Model: metacognitive-behavioral-tuning/Qwen3-0.6B-MBT-R
Source: Original Platform

README.md

@@ -0,0 +1,35 @@
+---
+base_model: Qwen/Qwen3-0.6B
+language:
+- en
+library_name: transformers
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- metacognitive-behavioral-tuning
+- multi-hop-qa
+- reasoning
+- sft
+- grpo
+- MBT-R
+---
+
+# Qwen3-0.6B · MBT-R
+
+MBT-R (main table) — **final checkpoint (SFT → GRPO)**. Base: [`Qwen/Qwen3-0.6B`](https://huggingface.co/Qwen/Qwen3-0.6B).
+Paper: *Metacognitive Behavioral Tuning of Large Language Models for Multi-Hop Question Answering*.
+
+- **Method**: MBT-R (Refinement): the student's own reasoning traces are rewritten into the 5-phase structure for SFT, then GRPO.
+- **Base model**: `Qwen/Qwen3-0.6B`
+- **Training**: SFT (LR 1e-4, BS 128, HotpotQA) → GRPO
+- **Benchmarks**: HotpotQA (ID), MuSiQue / 2WikiMultiHopQA (OOD)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+repo = "metacognitive-behavioral-tuning/Qwen3-0.6B-MBT-R"
+tok = AutoTokenizer.from_pretrained(repo)
+model = AutoModelForCausalLM.from_pretrained(repo, dtype="bfloat16", device_map="auto")
+```