The mutex-only run still collapsed at epoch 1 — same pattern as the DSS run. Val loss locks to log(8) ≈ 2.08 (uniform over the in-batch sat), train loss grows monotonically (4.80 → 5.56), train R@1 drops 7.79% → 0.34%. Mode collapse, not sampler-induced. The smoking gun is the queue: WeightedInfoNCELoss (the OLD-run loss) silently ignored `queue_negatives`, so the OLD-run effective task was in-batch-only contrast against 8 negatives. Switching to InfoNCELoss made the queue active — 4096 stale embeddings without a momentum encoder to keep them consistent with the live model. With the trimmed adapter surface (MONA in last 12/24 blocks → 3.5M trainable), the model can't reconcile fresh representations against stale negatives and collapses. Disable the queue entirely (`neg_bank_size = 0`). Matches OLD's effective setup — same 8 in-batch negatives, but with the new SymmetricInfoNCE + mutex sampler + tau clamp 0.1 + per-sample mask + full-gallery eval. Output → `out/gtauav/baseline_inbatch` (separate from the failed mutex run). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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