MIGRATION_PROGRESS.md

🚀 CodeLlama-7B Migration Progress Tracker

Started: November 25, 2025, 05:40 UTC
Status: 🟡 In Progress
Target: Complete migration with all critical + recommended updates

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📁 Folder Structure

codellama-migration/
├── models/
│   └── base-models/              # Base models directory
├── datasets/
│   ├── raw/                      # Original datasets (reference)
│   └── processed/                # CodeLlama-formatted datasets
├── training-outputs/             # Fine-tuned models will be saved here
├── scripts/                      # Updated scripts (symlinks/copies)
│   ├── training/
│   ├── inference/
│   └── api/
└── MIGRATION_PROGRESS.md         # This file

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✅ Progress Checklist

🔴 Critical Tasks

• Step 1: Download CodeLlama-7B-Instruct model

  • Status: ✅ COMPLETED
  • Target: codellama-migration/models/base-models/CodeLlama-7B-Instruct/
  • Size: 26GB (actual size)
  • Started: 2025-11-25 05:55 UTC
  • Completed: 2025-11-25 06:03 UTC
  • Notes: ✅ Download completed successfully!
  • Files: 52 files (config.json, tokenizers, model weights)
  • Formats: Both .safetensors and .bin formats available

• Step 2: Create CodeLlama-formatted dataset

  • Status: ✅ Completed (UPDATED)
  • Source: elinnos_fifo_mistral_100samples_converted.jsonl
  • Target: codellama-migration/datasets/processed/elinnos_fifo_codellama_v1.jsonl
  • Format: System prompt + task → verilog code (NO labels)
  • Started: 2025-11-25 05:54 UTC
  • Completed: 2025-11-25 06:00 UTC (UPDATED)
  • Notes: ✅ 94 samples reformatted, 125.6 KB file size
  • UPDATE: System prompt PRESERVED for domain specificity (removes generic responses)
  • KEY: Removed "System:" and "User:" labels to prevent conversational output

🟡 Recommended Tasks

• Step 3: Update inference script with code extraction

  • Status: ✅ Completed
  • File: codellama-migration/scripts/inference/inference_codellama.py
  • Changes:
    • ✅ Added extract_code_from_response() function
    • ✅ Changed default temperature: 0.7 → 0.3
    • ✅ Added code extraction to both streaming and non-streaming paths
  • Started: 2025-11-25 05:54 UTC
  • Completed: 2025-11-25 05:55 UTC
  • Notes: ✅ Code extraction handles verilog and generic markers

• Step 4: Document training parameters

  • Status: ✅ Documented
  • Parameters:
    • Epochs: 3 → 5
    • Learning Rate: 5e-5 → 2e-5
    • LoRA Rank: 32 → 64
    • LoRA Alpha: 64 → 128
    • Temperature: 0.7 → 0.3
  • Started: 2025-11-25 05:40 UTC
  • Completed: 2025-11-25 05:40 UTC
  • Notes: Parameters documented in migration plan

⚪ Optional Tasks

• Step 5: Update Gradio interface
  • Status: ⏳ Pending
  • File: semicon-finetuning-scripts/interface_app.py
  • Started: -
  • Completed: -
  • Notes: -

---

📊 Configuration Changes

Model Paths

• Old Base Model: /workspace/ftt/base_models/Mistral-7B-v0.1
• New Base Model: /workspace/ftt/codellama-migration/models/base-models/CodeLlama-7B-Instruct
• HuggingFace ID: codellama/CodeLlama-7b-Instruct-hf

Dataset Paths

• Old Dataset: elinnos_fifo_mistral_100samples_CLEAN_v2.jsonl
• New Dataset: codellama-migration/datasets/processed/elinnos_fifo_codellama_v1.jsonl

Training Parameters

• Epochs: 3 → 5
• Learning Rate: 5e-5 → 2e-5
• LoRA Rank: 32 → 64
• LoRA Alpha: 64 → 128
• Temperature: 0.7 → 0.3

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📝 Change Log

2025-11-25 05:40 UTC - Initial Setup

• ✅ Created folder structure
• ✅ Created this progress tracking document
• ⏳ Starting Step 1: Download CodeLlama model

2025-11-25 05:54 UTC - Dataset & Scripts Updated

• ✅ Step 2 COMPLETE: Created CodeLlama-formatted dataset
  • Source: elinnos_fifo_mistral_100samples_converted.jsonl
  • Output: codellama-migration/datasets/processed/elinnos_fifo_codellama_v1.jsonl
  • Format: Removed system prompt, added ```verilog markers
  • Samples: 94 reformatted successfully (100.5 KB)
• ✅ Step 3 COMPLETE: Updated inference script
  • Added extract_code_from_response() function (lines 24-58)
  • Changed default temperature: 0.7 → 0.3 (line 142)
  • Added code extraction to streaming path (line 193)
  • Added code extraction to non-streaming path (line 219)
  • File: codellama-migration/scripts/inference/inference_codellama.py
• ✅ Created symlinks for training scripts (no changes needed)
• ⏳ Step 1 in progress: CodeLlama download (PID: 29047)

2025-11-25 05:55 UTC - Download Started

• ✅ CodeLlama-7B-Instruct download initiated
• 📝 Download log: codellama-migration/download_log.txt
• ⏳ Estimated completion: 10-15 minutes

2025-11-25 06:00 UTC - Dataset Updated with System Prompt

• ✅ CRITICAL UPDATE: Dataset reformatted to KEEP system prompt
• Why: System prompt ensures domain-specific behavior and prevents generic responses
• Change:
  • ✅ System prompt content PRESERVED: "You are Elinnos RTL Code Generator..."
  • ❌ "System:" and "User:" LABELS removed (these triggered conversational mode)
  • ✅ Format: Clean instructional text + task → code
• Result: Best of both worlds - domain specificity + no conversation triggers
• File Size: 125.6 KB (increased from 100.5 KB due to system prompt)
• Sample Format:

  Instruction: "You are Elinnos... [system prompt]\n\nGenerate a FIFO..."
  Response: "```verilog\nmodule...```"
  

2025-11-25 06:03 UTC - CodeLlama Model Download Complete ✅

• ✅ Step 1 COMPLETE: CodeLlama-7B-Instruct successfully downloaded
• Location: codellama-migration/models/base-models/CodeLlama-7B-Instruct/
• Size: 26GB (52 files)
• Key Files:
  • ✅ config.json
  • ✅ tokenizer.json, tokenizer_config.json, tokenizer.model
  • ✅ model-00001-of-00002.safetensors (9.3GB)
  • ✅ model-00002-of-00002.safetensors (3.3GB)
  • ✅ pytorch_model-*.bin files (also available)
• Download Time: ~8 minutes (05:55 - 06:03 UTC)
• Status: ✅ READY FOR TRAINING

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🔧 Script Updates Status

Inference Script (inference_codellama.py)

• Code extraction function added
• Temperature default changed to 0.3
• Code marker removal logic implemented
• Tested with sample inference

Training Script

• ✅ No changes needed (model-agnostic)

API Server

• ✅ No changes needed (model-agnostic)

---

📈 Expected Outcomes

Metric	Current (Mistral)	Target (CodeLlama)
Code Generation Rate	16.7%	85-95%
Average Match Score	31.7%	75-85%
Conversational Output	Frequent	Rare/None

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🐛 Issues & Resolutions

Issues will be logged here as they occur

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📚 References

• Migration Plan: /workspace/ftt/CODELLAMA_MIGRATION_PLAN.md
• Comparison Report: /workspace/ftt/CLEAN_V2_TRAINING_COMPARISON_REPORT.md

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2025-11-25 06:14 UTC - Dataset Splitting & Validation Scripts Created

• ✅ Created: Dataset splitting script (scripts/dataset_split.py)
• ✅ Created: Dataset validation script (scripts/validate_dataset.py)
• ✅ Created: Comprehensive guide (DATASET_SPLIT_VALIDATION_GUIDE.md)
• Details:
  • Splitting happens BEFORE training (manual split recommended)
  • Script handles 75/10/15 split (train/val/test)
  • Validation checks: format, content, quality, duplicates
  • All CodeLlama-specific parameters documented

2025-11-25 06:15 UTC - Hyperparameter Analysis Complete

• ✅ Created: Complete hyperparameter analysis (HYPERPARAMETER_ANALYSIS.md)
• Dataset Analysis:
  • 94 samples, avg ~322 tokens per sample
  • All samples have code markers (100%)
  • Small dataset → needs regularization
• Optimized Parameters:
  • LoRA Rank: 48 (balance for code patterns + small dataset)
  • Learning Rate: 2e-5 (stability)
  • Epochs: 5 (more training needed)
  • Max Length: 1536 (efficiency, sufficient for dataset)
  • Dropout: 0.15 (more regularization)
• Efficiency:
  • Memory: ~6-7GB (fits easily in A100)
  • Training Time: ~8-10 minutes
  • Expected improvement: 75-85% match score

2025-11-25 06:41 UTC - Training Started with Optimized Hyperparameters

• ✅ Created: Enhanced training script (scripts/training/finetune_codellama.py)
  • Checkpoint resume support (automatic detection)
  • Incremental fine-tuning (continue from existing adapter)
  • Fresh training option
  • Uses pre-split train/val datasets
• ✅ Created: Training guide (TRAINING_GUIDE.md)
• ✅ Dataset Split: 75/10/15 (train/val/test) - 70/9/15 samples
• ✅ Training Started: CodeLlama fine-tuning with optimized hyperparameters
  • Base Model: CodeLlama-7B-Instruct
  • Output: training-outputs/codellama-fifo-v1
  • Hyperparameters: All optimized values from HYPERPARAMETER_ANALYSIS.md
  • Status: 🟢 TRAINING IN PROGRESS

Last Updated: 2025-11-25 06:41 UTC
Current Status: 🟢 TRAINING IN PROGRESS