caT-VTG

caT-VTG RLVR adapter, step 900

This is the exact complete checkpoint used by Team caT's final MARS2 2026 formal inference run videochat3-whisper-inference-20260731-180133-9b3e95.

• Base model: MCG-NJU/VideoChat3-4B
• Training: direct-base RLVR, eight GPUs
• Checkpoint: checkpoint-step-000900
• Adapter: LoRA rank 16, alpha 32, dropout 0.0
• Adapter weights SHA-256: fac5e9b635067e3046a6b26362cd5cbf3fc07bc558daaca86964e35b5f917dbd
• Complete checkpoint content SHA-256: 649abf427f52a0859f2eaae4ced5f34374384e52b4dfbb783f921ffc17b33ed1

The exact checkpoint is stored under checkpoint-step-000900/ so its original README.md can remain part of the immutable content identity while this repository keeps a separate Hugging Face model card. adapter_config.json and adapter_model.safetensors in that directory are sufficient for the portable reproduction runner in the companion GitHub repository. The optimizer, rank RNG, training-state, completion marker, and checkpoint manifest files are included so reviewers can also verify the original complete checkpoint identity.

The PEFT config is preserved byte-for-byte and therefore contains the absolute base model path from the training host. The companion loader first materializes the base model from MCG-NJU/VideoChat3-4B and then loads this adapter; it does not depend on that historical host path. Point the reproduction command at model/checkpoint-step-000900 after downloading this repository.

No official leaderboard score is claimed here. Use of the adapter is subject to the base model's license and the MARS2 competition data terms.