| """Kaggle notebook body: build the director's training set, fine-tune, re-score. |
| |
| Three subprocesses, same upgraded environment: |
| |
| 1. collect - sample the base model, keep every script that already satisfies the |
| TTS contract (acceptance is about 60% with the line format, so 160 scripts |
| costs roughly 35 minutes). |
| 2. train - fine-tune the last six blocks and the head on those 160. |
| 3. eval - score the tuned model on the same topic list as the baseline. |
| |
| Everything runs out-of-process because transformers has to be upgraded to 5.x |
| and this notebook already imported huggingface_hub to fetch the bundle. |
| """ |
| import os |
| import shutil |
| import subprocess |
| import sys |
|
|
| BUNDLE = "/kaggle/working/webfm-eval" |
| ENV = dict(os.environ, WORK_ROOT="/kaggle/working") |
|
|
|
|
| def sh(cmd: str) -> None: |
| print(f"$ {cmd}", flush=True) |
| if subprocess.run(cmd, shell=True).returncode != 0: |
| raise SystemExit(f"failed: {cmd}") |
|
|
|
|
| def run(script: str, **env) -> int: |
| target = os.path.join(BUNDLE, "kaggle", script) |
| print(f"\n===== {script} {env} =====", flush=True) |
| rc = subprocess.run([sys.executable, target], env=dict(ENV, **env)).returncode |
| print(f"----- {script} rc={rc} -----", flush=True) |
| return rc |
|
|
|
|
| def main() -> None: |
| sh("pip install -q --upgrade 'transformers>=5' 'huggingface_hub>=1.31,<2' accelerate") |
|
|
| if not os.path.exists(os.path.join(BUNDLE, "kaggle", "director_probe.py")): |
| raise SystemExit("director_probe.py missing") |
|
|
| |
| |
| seed = os.path.join(BUNDLE, "director", "sft.jsonl") |
| if os.path.exists(seed): |
| os.makedirs("/kaggle/working/director", exist_ok=True) |
| shutil.copyfile(seed, "/kaggle/working/director/sft.jsonl") |
| print("reusing collected scripts", flush=True) |
| else: |
| run("director_probe.py", MODE="collect", TARGET="160", MAX_TRIES="700") |
| if run("director_sft.py", EPOCHS="4", TRAIN_LAYERS="6") != 0: |
| raise SystemExit("training failed") |
| run("director_probe.py", MODE="eval", N_SAMPLES="12", |
| DIRECTOR_MODEL="/kaggle/working/director/model") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
