base_model: google/gemma-4-E4B-it
library_name: peft
license: apache-2.0
tags:
- gemma4
- coding
- qlora
- kaggle-proof
Gemma 4 E4B IT Coding LoRA
QLoRA adapter for google/gemma-4-E4B-it, trained on filtered benign coding instructions.
Training
- Runtime: Kaggle 2x Tesla T4
- Data: filtered benign coding instruction data
- Safe rows used: 1024
- Steps: 200
- LoRA: r=16, alpha=32, target_modules=
all-linear - Trainable parameters: 50,499,584
- Final train loss: 1.1427
50-Problem HumanEval Proof
This adapter was merged into josephmayo/gemma-4-E4B-it-Coder and evaluated on Kaggle with 2x Tesla T4 GPUs using an executable 50-task HumanEval subset. Full generated before/after code is published in eval50_before_after_full_code.csv.
| Metric | Base google/gemma-4-E4B-it |
Coder merge |
|---|---|---|
| Pass count | 34 / 50 | 42 / 50 |
| Absolute lift | - | +16.0 pp |
| Relative pass-count lift | - | +23.53% |
Proof files included here: eval50_summary.json, eval50_before_after_full_code.csv, EVAL50_README.md, nvidia_smi.txt.
Earlier 8-task smoke artifacts are still included for reproducibility (eval_before_after.csv, executable_eval.json, trainer_log_history.json, summary.json, proof_summary.json, evaluation_scope.json), but the headline proof is the 50-task executable run above.
This adapter is for benign coding assistance only. It was not trained on malware, phishing, exploit, credential theft, evasion, or destructive automation examples.