Robotics
PyTorch
Cosmos
xperience10m_task_baseline_suite
embodied-ai
multimodal
xperience-10m
baseline
evaluation
qwen3-omni
Instructions to use cy0307/ropedia-xperience-10m-task-baselines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use cy0307/ropedia-xperience-10m-task-baselines with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
ropedia-xperience-10m-task-baselines / results /episode_task_suite /neural_mlp /caption_grounding /metrics.json
| { | |
| "mrr": 0.01684125567132316, | |
| "median_rank": 180.5, | |
| "mean_rank": 178.382183908046, | |
| "num_queries": 348, | |
| "top1_accuracy": 0.0028735632183908046, | |
| "top5_accuracy": 0.014367816091954023, | |
| "top10_accuracy": 0.020114942528735632, | |
| "task": "caption_grounding", | |
| "input": "caption objects/interaction text query + candidate sensor windows", | |
| "split": "chronological", | |
| "num_train_windows": 813, | |
| "num_test_windows": 348, | |
| "target_dim": 896, | |
| "output": "matching time window", | |
| "model": "neural_mlp", | |
| "head": "z-score -> MLP projection/regression", | |
| "neural_epochs": 80, | |
| "neural_hidden_dim": 128, | |
| "neural_batch_size": 128, | |
| "neural_learning_rate": 0.001, | |
| "neural_weight_decay": 0.0001, | |
| "neural_dropout": 0.1, | |
| "neural_device": "cpu", | |
| "train_final_loss": 0.06317874967483723, | |
| "task_display_name": "Language Grounding" | |
| } | |