Instructions to use alexis779/so100_cube_rectangle_day_reward_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use alexis779/so100_cube_rectangle_day_reward_classifier with LeRobot:
- Notebooks
- Google Colab
- Kaggle
| { | |
| "dataset": { | |
| "repo_id": "alexis779/so100_cube_rectangle_day", | |
| "root": null, | |
| "episodes": null, | |
| "image_transforms": { | |
| "enable": false, | |
| "max_num_transforms": 3, | |
| "random_order": false, | |
| "tfs": { | |
| "brightness": { | |
| "weight": 1.0, | |
| "type": "ColorJitter", | |
| "kwargs": { | |
| "brightness": [ | |
| 0.8, | |
| 1.2 | |
| ] | |
| } | |
| }, | |
| "contrast": { | |
| "weight": 1.0, | |
| "type": "ColorJitter", | |
| "kwargs": { | |
| "contrast": [ | |
| 0.8, | |
| 1.2 | |
| ] | |
| } | |
| }, | |
| "saturation": { | |
| "weight": 1.0, | |
| "type": "ColorJitter", | |
| "kwargs": { | |
| "saturation": [ | |
| 0.5, | |
| 1.5 | |
| ] | |
| } | |
| }, | |
| "hue": { | |
| "weight": 1.0, | |
| "type": "ColorJitter", | |
| "kwargs": { | |
| "hue": [ | |
| -0.05, | |
| 0.05 | |
| ] | |
| } | |
| }, | |
| "sharpness": { | |
| "weight": 1.0, | |
| "type": "SharpnessJitter", | |
| "kwargs": { | |
| "sharpness": [ | |
| 0.5, | |
| 1.5 | |
| ] | |
| } | |
| }, | |
| "affine": { | |
| "weight": 1.0, | |
| "type": "RandomAffine", | |
| "kwargs": { | |
| "degrees": [ | |
| -5.0, | |
| 5.0 | |
| ], | |
| "translate": [ | |
| 0.05, | |
| 0.05 | |
| ] | |
| } | |
| } | |
| } | |
| }, | |
| "revision": null, | |
| "use_imagenet_stats": true, | |
| "video_backend": "torchcodec", | |
| "return_uint8": false, | |
| "streaming": false | |
| }, | |
| "env": null, | |
| "policy": null, | |
| "reward_model": { | |
| "type": "reward_classifier", | |
| "input_features": { | |
| "observation.images.side": { | |
| "type": "VISUAL", | |
| "shape": [ | |
| 3, | |
| 128, | |
| 128 | |
| ] | |
| }, | |
| "observation.images.wrist": { | |
| "type": "VISUAL", | |
| "shape": [ | |
| 3, | |
| 128, | |
| 128 | |
| ] | |
| } | |
| }, | |
| "output_features": {}, | |
| "device": "cpu", | |
| "pretrained_path": null, | |
| "push_to_hub": true, | |
| "repo_id": "alexis779/so100_cube_rectangle_day_reward_classifier", | |
| "license": null, | |
| "tags": null, | |
| "private": null, | |
| "name": "reward_classifier", | |
| "num_classes": 2, | |
| "hidden_dim": 256, | |
| "latent_dim": 256, | |
| "image_embedding_pooling_dim": 8, | |
| "dropout_rate": 0.1, | |
| "model_name": "helper2424/resnet10", | |
| "model_type": "cnn", | |
| "num_cameras": 2, | |
| "learning_rate": 0.0001, | |
| "weight_decay": 0.01, | |
| "grad_clip_norm": 1.0, | |
| "normalization_mapping": { | |
| "VISUAL": "MEAN_STD" | |
| } | |
| }, | |
| "output_dir": "outputs/train/2026-06-10/18-46-57_reward-classifier", | |
| "job_name": "reward-classifier", | |
| "resume": false, | |
| "seed": 2, | |
| "cudnn_deterministic": false, | |
| "num_workers": 4, | |
| "batch_size": 16, | |
| "prefetch_factor": 4, | |
| "persistent_workers": true, | |
| "steps": 5000, | |
| "eval_freq": 1000, | |
| "log_freq": 10, | |
| "tolerance_s": 0.0001, | |
| "save_checkpoint": true, | |
| "save_freq": 1000, | |
| "use_policy_training_preset": true, | |
| "optimizer": { | |
| "type": "adamw", | |
| "lr": 0.0001, | |
| "weight_decay": 0.01, | |
| "grad_clip_norm": 1.0, | |
| "betas": [ | |
| 0.9, | |
| 0.999 | |
| ], | |
| "eps": 1e-08 | |
| }, | |
| "scheduler": null, | |
| "eval": { | |
| "n_episodes": 50, | |
| "batch_size": 8, | |
| "use_async_envs": true | |
| }, | |
| "wandb": { | |
| "enable": true, | |
| "disable_artifact": false, | |
| "project": "slobot-hilserl", | |
| "entity": null, | |
| "notes": null, | |
| "run_id": "fq3whe5r", | |
| "mode": null, | |
| "add_tags": true | |
| }, | |
| "peft": null, | |
| "sample_weighting": null, | |
| "rename_map": {}, | |
| "checkpoint_path": null | |
| } |