pendulum-causal-qa-3000 / data /metadata.json
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Add pendulum causal QA 3K annotations, OOD validation and demo videos
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{
"dataset": "pendulum_causal_qa",
"version": "1.0",
"source_dataset": "https://huggingface.co/datasets/jimchen2/pendulum-cjepa-160f",
"num_videos": 3000,
"train_videos": 2400,
"val_videos": 600,
"validation_groups": {
"in_distribution": 2400,
"val_ood_amplitude": 100,
"val_ood_near_conservative": 100,
"val_ood_initial_velocity": 100,
"val_ood_gravity_length": 100,
"val_ood_illumination": 100,
"val_ood_compound": 100
},
"num_questions_per_video": 14,
"num_questions": 42000,
"videos_generated": false,
"timeseries_generated": false,
"question_types": [
"descriptive",
"predictive",
"explanatory",
"counterfactual"
],
"frames_per_video": 160,
"fps": 12,
"duration_s": 13.333333333333334,
"size_px": [
196,
196
],
"substeps_per_frame": 8,
"integrator": "RK4",
"ode": "theta_ddot = -(gravity/length)*sin(theta) - damping*theta_dot",
"train_seed": 42,
"validation_protocol": "Whole-video, six-stratum OOD holdout. Validation parameters use fixed low-discrepancy schedules independent of --seed; see README and index.csv.",
"split_unit": "whole video",
"qa_files": [
"questions.jsonl",
"questions.csv"
],
"timing": "CSV row n and decoded MP4 frame n sample time n/fps",
"audio": false,
"renderer": "upstream pendulum-cjepa-160f renderer, fixed visual rod length"
}