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fix: use Path(output_dir) before 'out' is defined in train()
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#148:
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fix: resume_ckpt NameError in train() - use output_dir/latest instead
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fix: save/load optimizer+scheduler+scaler on checkpoint resume; fix -…
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eval kernel: force T4 via machine_shape=NvidiaTeslaT4 (P100 default o…
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eval_768: make repo root importable for tinydoc_vlm (fixes Kaggle run)
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#144:
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kaggle notebook: single-GPU by default (DDP SIGSEGVs on T4 x2; kaggle…
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kaggle: retry HF_TOKEN secrets fetch with backoff; fix token injectio…
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run_kaggle.sh: BATCH default 8 -> 2 (matches notebook's memory-safe d…
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train on T4 x2 via DDP; fresh-start from empty hub checkpoint repo
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#140:
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CRITICAL FIX: collate_fn only injected 1 <image> token — model never …
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fix: suppress HTTP logs, fix opt.zero_grad bug, single T4, always re-…
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#138:
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kaggle: fix torch-pin install (cu124 index dropped cudnn 9.1.0.70)
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kaggle: auto-relaunch on signal-death (VM kills trainer every ~40 min)
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kaggle: pin torch 2.6.0+cu124 on T4 (4x SIGSEGV on image torch 2.10)
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kaggle: single-GPU first; DDP opt-in (3x SIGSEGV today)
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#134:
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kaggle: add single-GPU last-resort fallback after DDP SIGSEGV
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#133:
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kaggle: remove fp16-only dtype guard (would discard new fp32 checkpoi…
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kaggle: self-healing memory plan - grad-ckpt first, batch-1 fallback …
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kaggle: enable grad-checkpointing (fp32 master weights OOM the 14.5Gi…
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fix: NaN cascade from half-precision AdamW state (root cause of every…
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#129:
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fix: args -> num_workers inside train() function
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amp: add --num-workers arg (default 0 for MPS, 2 for CUDA); kaggle us…
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#127:
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kaggle: disable grad-checkpoint (SIGSEGV trigger on T4) and use num_w…
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amp: split autocast vs scaler — always autocast on CUDA for numerical…
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amp: only use GradScaler with fp32 params (fp16/bf16 checkpoints -> f…
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#124:
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