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: 714 Bytes
540e67a eeac43c 540e67a eeac43c 540e67a eeac43c 540e67a eeac43c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # Qwen3-Omni LoRA Training
- Base model: `<workspace-parent>/modelscope_models/Qwen__Qwen3-Omni-30B-A3B-Instruct`
- Dataset run: `xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605`
- Training run: `xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_lora`
- Checkpoint: `<project>/checkpoints/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_lora/adapter_lora`
- Processes: `8`
- Train samples: `2848`
- Validation samples: `512`
- Epochs: `1`
- Global step: `356`
- Train loss: `0.413046`
- Validation loss: `0.033066`
This is the validation-aware diagnostic run. Raw Xperience-10M files, base-model weights, and adapter weights are not committed to this repo.
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