File size: 2,037 Bytes
fc48e53 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | ---
dataset_info:
features:
- name: text
dtype: string
- name: video
dtype: string
- name: hard_negative_texts
list: string
- name: hard_negative_videos
list: string
splits:
- name: train
num_bytes: 956204969
num_examples: 2700
download_size: 956204969
dataset_size: 956204969
configs:
- config_name: default
data_files:
- split: train
path: metadata.parquet
---
# Physics Bench Solid Train
Repository: `gowitheflowlab/physics-bench-solid-train`
Training split with hard negatives for solid simulation video retrieval.
- rows: 2700
- metadata columns: `text`, `video`, `hard_negative_texts`, `hard_negative_videos`
- hard negatives per row: 5, drawn from the other 99 cases of the same family
- video paths: repository-relative `videos/<family>/<case_id>.mp4`
- list alignment: `hard_negative_texts[i]` and `hard_negative_videos[i]` come from the same case
- `text` and `hard_negative_texts` use the natural-language query style (`solid_eval_queries_v4_dynamics_aligned_raw_parsed`),
matching the `parsed_text` column of `gowitheflowlab/physics-bench-solid-eval-2700`
- case parameters are disjoint from the evaluation split, so no evaluation case is reachable here
## Reproducibility
- sampling: global seed 42, family alphabetical order then case_id order, one
`random.Random(seed)` stream, `random.sample(sorted(other_99_case_ids), 5)`
- assignment digest: `a9c1db6e65fb206f`
- text: generated from the training case metadata; see
`source_metadata/build_hardnegs_v2_metadata.py` and `source_metadata/v2_manifest.json`
- validation report: `quality/validation.json`
## Loading
```python
from pathlib import Path
import pyarrow.parquet as pq
from huggingface_hub import snapshot_download
root = Path(snapshot_download("gowitheflowlab/physics-bench-solid-train", repo_type="dataset"))
rows = pq.read_table(root / "metadata.parquet").to_pylist()
row = rows[0]
positive_video = root / row["video"]
negative_videos = [root / path for path in row["hard_negative_videos"]]
```
|