Nanochat Training Monitoring and Analysis

Nanochat Training Monitoring and Analysis | Generated by AI

Home 2026.06
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         SESSION SUMMARY — Nanochat Training Monitoring
         Date: 2026-06-06 (Fri)
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1. MONITORED TRAINING (nanochat d12, 286M params)
   - Checked tmux sessions on lzw workstation (RTX 4070)
   - Training was in tmux 0 (not 7 or 12 as initially asked)
   - LAN IP became unreachable — switched to Tailscale
   - Checked 3 times over ~2 hours:
     * 60,841/87,000 (70%) → loss 2.99, ETA 8.5h
     * 66,141/87,000 (76%) → loss 2.91, ETA 6.8h
     * 71,641/87,000 (82%) → loss 2.90, ETA 5h
   - Training completed at 4:58 AM: 87,000 steps, 28.4h, val_bpb=0.8658

2. TRAINING ANALYSIS
   - Extracted checkpoint metadata (9 checkpoints: 10k-87k)
   - Built loss progression table (val_bpb, smooth_train_loss)
   - Documented model architecture: 286M params, 12 layers, 768 dim,
     6 heads, RoPE, QK norm, ReLU², Value Embeddings, window=L
   - Documented optimizer: MuonAdamW, cosine LR schedule, warmdown 65%
   - Phase 1 (0-10k): fineweb-edu-d12, from scratch
   - Phase 2 (10k-87k): rtx4070-d12-chinchilla, resumed

3. EXTENDED TRAINING PLANNING (87k → 130k)
   - Analyzed LR schedule implications (warmdown ratio issue)
   - Identified LR spike risk on resume (0 → 0.53 at step 87k)
   - Provided 3 options (resume, retrain, extended warmdown)
   - Gave command with --depth 12 --window-pattern L

4. TROUBLESHOT RESUME ISSUES
   - FileNotFoundError: d20/model_087000.pt — fixed with --depth 12
   - OOM during torch.compile — fixed with TORCH_COMPILE_DISABLE=1
   - Added --window-pattern L as requested

5. GENERATED SAMPLE TEXT
   - Loaded checkpoint step 87k, generated from 10 prompts
   - Quality: decent prose, weak at code, repetition loops
   - Saved samples to /mnt/data/zz/logs/nanochat_samples_step87k.txt

6. SAVED LOGS & PUSHED TO HUGGINGFACE
   - Saved tmux scrollback + checkpoint metadata to /mnt/data/zz/logs/
   - Moved train logs to proper logs/ directory
   - Committed & pushed zz dataset to HuggingFace
   - Committed & pushed nanochat to GitHub
   - Pushed sample outputs run2 to HuggingFace

7. PUSHING MODEL TO HUGGINGFACE MODELS
   - Prepared /tmp/nanochat-upload/ with final model (757MB) + metadata
   - Created README.md model card
   - Pushing to HuggingFace Models

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KEY ARTIFACTS
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  Workstation: /mnt/data/nanochat/ — training code + checkpoints
  Logs dir:    /mnt/data/zz/logs/  — all training logs
  Script:      /mnt/data/nanochat/scripts/analysis/generate_samples.py
  HF Dataset:  https://huggingface.co/datasets/lzwjava/zz
  HF Model:    https://huggingface.co/lzwjava/nanochat-d12 (pending)
  GitHub:      https://github.com/lzwjava/nanochat
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