- Modified reward_extraction to accept prompt_text and cross-check predicted sentiment against nota (review rating)
- Penalize -0.20 when nota ≤ 2 (negative) but sentiment is "positive", or nota ≥ 4 (positive) but sentiment is "negative"
- Reduced task weight cap from 0.60 to 0.50 for more conservative weight updates
- Updated both reward_extraction calls to pass original prompt text
- Reformatted audit cell for better readability
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
v4: ROOT CAUSE FIX — use standard PEFT not Unsloth get_peft_model (fused LoRA kernels have dtype bug #4891). Revert to load_in_4bit=True, dtype=None matching V3.
Single-model validation on Tucano2-qwen-0.5B-Instruct with all four
task types. Key changes from V3: no <think> overhead, G=16, 512-token
completions, continuous reward design, hard clip_ratio probe gate,
and all generation_config bug fixes (rep_penalty, top_k, use_cache).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
apply v3 task-aware thinking controls and delete deprecated notebook
- Replaced monolithic SYSTEM_PT with task-specific system prompts to guide verbosity and thinking mode per task.
- Integrated reward_think_efficiency in the reward function dispatch to penalize bloated thinking depending on task budgets.
- Added dynamic system prompt injection into calibration, dataset preparation, and validation loops.
- Deleted deprecated notebooks/DEPRECATED_grpo_vertex_v3.ipynb.