# Sweep Experiment Scripts (Jul 9 2026)

All LR sweep scripts for FFT on `generated_data.jsonl` (1314 real API texts).

## File Naming Convention
- `train_per_token_vali_overfi_roberta_lr*.py` — RoBERTa-large fresh HF backbone, 4 LR sweep
- `train_per_token_vali_overfi_deberta_lr*.py` — DeBERTa-v3-large SN32 weights, 5 LR sweep
- `train_per_token_vali_trndffi_overfi_lr*.py` — RoBERTa-large transfer (from synthetic sandwich ckpt), 5 LR sweep
- `train_per_token_vali_overfi_base.py` — Clean base template (patience=1000, epoch ckpts)
- `train_per_token_vali_overfi_deberta.py` — DeBERTa SN32 base template
- `train_per_token_vali_trndffi_overfi.py` — Transfer base template

## Results Summary
| Config | LR | Best Reward |
|--------|----|-------------|
| RoBERTa fresh | 1e-5 | 0.8347 |
| RoBERTa trndffi | 1e-5 | 0.8570 ← winner |
| RoBERTa trndffi | 1e-6 | 0.8005 |
| DeBERTa SN32 | any | ~0.37 (F1=0 all LRs) |

See `AGENTS_BUCKT_TRAIN.md` section 16 for full analysis.