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MIGRATION_PROGRESS.md

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+# 🚀 CodeLlama-7B Migration Progress Tracker
+
+**Started:** November 25, 2025, 05:40 UTC  
+**Status:** 🟡 In Progress  
+**Target:** Complete migration with all critical + recommended updates
+
+---
+
+## 📁 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
+```
+
+---
+
+## ✅ Progress Checklist
+
+### 🔴 Critical Tasks
+
+- [x] **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
+
+- [x] **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
+
+- [x] **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
+
+- [x] **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**
+
+---
+
+## 📝 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**
+
+---
+
+## 🔧 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 |
+
+---
+
+## 🐛 Issues & Resolutions
+
+_Issues will be logged here as they occur_
+
+---
+
+## 📚 References
+
+- Migration Plan: `/workspace/ftt/CODELLAMA_MIGRATION_PLAN.md`
+- Comparison Report: `/workspace/ftt/CLEAN_V2_TRAINING_COMPARISON_REPORT.md`
+
+---
+
+### 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**
+