| # HFA Parameter Mapping Debug Output | |
| ## Issue | |
| HFA model produces random predictions with extremely low probabilities (~0.000008) despite successful checkpoint loading. | |
| ## Analysis Date | |
| 2025-09-15 04:26:52 | |
| ## Files | |
| - `hfa_parameter_debug_*.txt`: Complete debug output | |
| - `hfa_parameter_analysis_*.json`: Structured analysis data | |
| ## Problem | |
| The model configuration matches checkpoint dimensions (256 hidden, 8 heads, 6 layers) but parameters aren't loading correctly, resulting in random predictions instead of meaningful language modeling. | |
| ## Next Steps | |
| 1. Verify exact parameter name mapping between checkpoint and model | |
| 2. Check if critical parameters (embedding, attention, lm_head) are being loaded | |
| 3. Ensure parameter values are being copied correctly (not just shapes) | |