src/README.md

src/

The training + evaluation code. This is the primary thing we want to read — it's the only way to confirm what the Claude-written report actually did.

Files to push

file	what it is
train_head.py	LoRA + prototype-head training
evaluate.py	metrics: top-1 accuracy, macro-F1, show/hide, confidence buckets
rules_table.json	the fixed step-4 show/hide rules (no AI)
config.yaml	all hyperparameters (see the checklist in the root README)

Also include so it runs offline

• requirements.txt (or environment.yml) — torch version, bf16 support, transformers/peft versions
• a short how-to-run: base model path (Qwen/Qwen3-Embedding-0.6B), seed flag, config flag, output paths
• any preprocessing that turns a raw item into the model input (concatenation order, tokenization, max length)

What we'll check in train_head.py (vs the root README checklist)

LoRA rank/alpha/dropout + which modules · prototype head + cosine×scale + scale init 20 · prototype seeding from description embeddings · loss + label smoothing · the two AdamW groups + warmup/decay · early-stop on val macro-F1 · class-balanced sampling + hard-pair weighting · seed handling.