| dataset_info: | |
| config_name: robometer_failure_detection | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: task | |
| dtype: string | |
| - name: lang_vector | |
| list: float32 | |
| - name: data_source | |
| dtype: string | |
| - name: frames | |
| dtype: string | |
| - name: is_robot | |
| dtype: bool | |
| - name: quality_label | |
| dtype: string | |
| - name: preference_group_id | |
| dtype: 'null' | |
| - name: preference_rank | |
| dtype: 'null' | |
| - name: partial_success | |
| dtype: 'null' | |
| splits: | |
| - name: train | |
| num_bytes: 175273 | |
| num_examples: 100 | |
| download_size: 28483 | |
| dataset_size: 175273 | |
| configs: | |
| - config_name: robometer_failure_detection | |
| data_files: | |
| - split: train | |
| path: robometer_failure_detection/train-* | |
| # Robometer Failure Detection Dataset | |
| The exact **100 videos** that the reported Robometer failure-detection results are | |
| computed on: 81 trajectories across 7 tasks, external and wrist views (43 ext / 57 | |
| wrist), labels `successful` / `suboptimal` / `failure` (suboptimal counted as failure | |
| at evaluation time). | |
| Tasks: foldtowel, movebanana, movemouse, pourpebble, pulltissue, putspoon, stirpot. | |
| ## Metric note | |
| Reported F1 uses **failure as the positive class**, and the "Average" row is pooled over | |
| all videos (not a macro-average over tasks). | |
| ## Usage | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("myconnects/robometer_failure_detection", | |
| "robometer_failure_detection", split="train") | |
| ``` | |