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
File size: 603 Bytes
540e67a eeac43c 540e67a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # Qwen3-Omni LoRA Evaluation
- Base model: `<workspace-parent>/modelscope_models/Qwen__Qwen3-Omni-30B-A3B-Instruct`
- Adapter: `<project>/checkpoints/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_lora/adapter_lora`
- Dataset: `<project>/results/omni_finetune/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_dataset/dataset.jsonl`
- Eval split: `test`
- Samples: `448`
- Episodes: `14`
- Accuracy: `0.0246`
- Macro-F1: `0.0027`
- Unseen eval labels: `144`
Artifacts include `metrics.json`, `predictions.csv`, `per_class_metrics.csv`, and `confusion_matrix.csv`.
|