| # Reproduce the pilot |
|
|
| Use a Linux GPU environment matching `environment.txt`. This is the exact |
| training source; dependency versions and data hashes are in `training.json`. |
| Hardware and numerical differences can change the selected checkpoint. |
|
|
| Download the foundation at its pinned revision and this release's synthetic |
| train/validation data. Run from this directory; choose a new output directory. |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| "vllm-sr/Vela-1.0-Encoder-307M", |
| revision="720ab37904ce15054068d429381bfae7549f00f6", |
| local_dir="base", |
| ) |
| snapshot_download( |
| "TwilightTechie/commitment-statements-pilot", repo_type="dataset", local_dir="dataset" |
| ) |
| ``` |
|
|
| ```bash |
| python -m sequence_repair.train \ |
| --method full --fresh-head --trainable-last-layers 2 \ |
| --base base --base-id vllm-sr/Vela-1.0-Encoder-307M \ |
| --base-revision 720ab37904ce15054068d429381bfae7549f00f6 \ |
| --contract ../label-contract.json \ |
| --train dataset/data/train.jsonl --dev dataset/data/validation.jsonl \ |
| --output rerun --steps 100 --batch-size 2 --accumulate 2 \ |
| --max-length 256 --learning-rate 0.00002 --head-learning-rate 0.0001 \ |
| --eval-every 25 --evaluation-dtype float32 --selection macro-f1 --seed 42 |
| ``` |
|
|
| The original run selected step 75 using development macro F1. No reserved test |
| examples are distributed or used by this command. Before running, verify the |
| training and validation file hashes against `training.json`. |
|
|
