# Generated data

Training sets we generated or augmented for the released models. Each row is `text, target, stance`
with `stance` in `{Favor, Against, None}`. Paths match what the configs and training scripts expect,
so run them with this folder as the data root.

| File | Rows | How it was made | Used by |
|---|---|---|---|
| `track2/train_aug.csv` | 8,056 | Track-2 train plus LLM paraphrases; a `source` column marks `original` (2,714) or `paraphrase` (5,342) | encoder `t2_marbert_aug`, via `configs/track2_aug.yaml` |
| `synth/t1_train_style.csv` | 3,902 | Track-1 train plus style-grounded generated shots | LoRA `allam_style` |
| `external/pool_real_all.csv` | 4,449 | pooled real-target shots (Women Empowerment, Covid, Digital) | LoRA `allam_real` |

The official Mawqif-v2 splits belong to the organizers and are not redistributed here. Get them from
the shared task at https://stanceeval.github.io/. Everything above is derived from those splits and
can be regenerated:

```bash
python -m src.gen_synth  --help      # style and target-matched shot pools
python -m src.augment    --help      # paraphrase augmentation
```