Instructions to use H2Ozone/lever_reach_act3phase_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use H2Ozone/lever_reach_act3phase_v1 with LeRobot:
- Notebooks
- Google Colab
- Kaggle
| { | |
| "selection_metric": "mean held-out ACT loss", | |
| "phases": { | |
| "reach": { | |
| "candidates": [ | |
| { | |
| "step": 2500, | |
| "val_loss": 0.12390706464648246, | |
| "samples": 640, | |
| "path": "reach/checkpoints/002500/pretrained_model" | |
| }, | |
| { | |
| "step": 5000, | |
| "val_loss": 0.12380270436406135, | |
| "samples": 640, | |
| "path": "reach/checkpoints/005000/pretrained_model" | |
| }, | |
| { | |
| "step": 7500, | |
| "val_loss": 0.12385439872741699, | |
| "samples": 640, | |
| "path": "reach/checkpoints/007500/pretrained_model" | |
| }, | |
| { | |
| "step": 10000, | |
| "val_loss": 0.12326513081789017, | |
| "samples": 640, | |
| "path": "reach/checkpoints/010000/pretrained_model" | |
| } | |
| ], | |
| "selected": { | |
| "step": 10000, | |
| "val_loss": 0.12326513081789017, | |
| "samples": 640, | |
| "path": "reach/checkpoints/010000/pretrained_model" | |
| } | |
| }, | |
| "push_down": { | |
| "candidates": [ | |
| { | |
| "step": 2500, | |
| "val_loss": 0.08102959766983986, | |
| "samples": 640, | |
| "path": "push_down/checkpoints/002500/pretrained_model" | |
| }, | |
| { | |
| "step": 5000, | |
| "val_loss": 0.08040141463279724, | |
| "samples": 640, | |
| "path": "push_down/checkpoints/005000/pretrained_model" | |
| }, | |
| { | |
| "step": 7500, | |
| "val_loss": 0.08016956225037575, | |
| "samples": 640, | |
| "path": "push_down/checkpoints/007500/pretrained_model" | |
| }, | |
| { | |
| "step": 10000, | |
| "val_loss": 0.08095664083957672, | |
| "samples": 640, | |
| "path": "push_down/checkpoints/010000/pretrained_model" | |
| } | |
| ], | |
| "selected": { | |
| "step": 7500, | |
| "val_loss": 0.08016956225037575, | |
| "samples": 640, | |
| "path": "push_down/checkpoints/007500/pretrained_model" | |
| } | |
| }, | |
| "finish_lowering": { | |
| "candidates": [ | |
| { | |
| "step": 2500, | |
| "val_loss": 0.05731681007891894, | |
| "samples": 640, | |
| "path": "finish_lowering/checkpoints/002500/pretrained_model" | |
| }, | |
| { | |
| "step": 5000, | |
| "val_loss": 0.05829748827964067, | |
| "samples": 640, | |
| "path": "finish_lowering/checkpoints/005000/pretrained_model" | |
| }, | |
| { | |
| "step": 7500, | |
| "val_loss": 0.0587701179087162, | |
| "samples": 640, | |
| "path": "finish_lowering/checkpoints/007500/pretrained_model" | |
| }, | |
| { | |
| "step": 10000, | |
| "val_loss": 0.058973603509366514, | |
| "samples": 640, | |
| "path": "finish_lowering/checkpoints/010000/pretrained_model" | |
| } | |
| ], | |
| "selected": { | |
| "step": 2500, | |
| "val_loss": 0.05731681007891894, | |
| "samples": 640, | |
| "path": "finish_lowering/checkpoints/002500/pretrained_model" | |
| } | |
| } | |
| } | |
| } | |