| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - evaluation |
| - video |
| - multimodal |
| --- |
| |
| # CleverHans-Evaluation |
|
|
| Scripts and a small in-domain test set to evaluate Qwen3-Omni variants on **Video-MME**, **LVBench**, and **audio–video sync** (custom JSONL). |
|
|
| ## What’s in the repo |
|
|
| | Path | Purpose | |
| |------|---------| |
| | `setup_env.sh` | Installs **Anaconda** if conda is missing, then creates `video` (or `CONDA_ENV`) and pip-installs eval deps | |
| | `setup_data.sh` | Downloads **all** eval data: Video-MME, LVBench, and sync eval videos + audio (to `/opt/dlami/nvme`) | |
| | `COMMANDS.md` | Copy-paste commands: data download, merge, eval per model/dataset | |
| | `data/kto_training_data_v2_test.jsonl` | In-domain sync test (426 lines) | |
| | `scripts/*.py` | Download, merge, eval, metrics helpers | |
|
|
| ## Quick start |
|
|
| ```bash |
| git clone https://huggingface.co/Rakancorle11/CleverHans-Evaluation |
| cd CleverHans-Evaluation |
| |
| huggingface-cli login # if needed for gated models |
| |
| chmod +x setup_env.sh setup_data.sh |
| bash setup_env.sh # on a machine with no conda: downloads Anaconda to ~/anaconda3 first |
| source ~/anaconda3/etc/profile.d/conda.sh # if this is your first shell after install |
| conda activate video |
| |
| bash setup_data.sh # downloads Video-MME, LVBench, sync videos + audio to /opt/dlami/nvme |
| |
| # Then follow COMMANDS.md — you choose which model on which benchmark. |
| ``` |
|
|
| **Fresh OS notes:** install `wget` before running (`sudo apt install -y wget`). System **ffmpeg** is recommended (`sudo apt install -y ffmpeg`). Override `INSTALL_DIR` / `ANACONDA_VERSION` / `CUDA_INDEX_URL` via environment variables if needed (see comments in `setup_env.sh`). |
|
|
| ## Models (HF IDs) |
|
|
| | Role | Model | |
| |------|--------| |
| | Vanilla | `Qwen/Qwen3-Omni-30B-A3B-Instruct` | |
| | Full SFT (merge / eval base) | `Rakancorle11/qwen3omni_full_sft_revised_thinker_key` | |
| | DPO LoRA | `Rakancorle11/Qwen3Omni-onpolicy-dpo-lora-w_audio_v2_8632`, `_v3_8632`, `_v4_8632`, `_v5_12075` | |
|
|
| Merge LoRA into a full checkpoint for **vLLM** with `scripts/merge_adapter.py`. For **transformers-only** Video-MME/LVBench you can pass `--adapter` instead of merging. |
|
|
| ## Data |
|
|
| - **Video-MME / LVBench / Sync eval data**: all downloaded by `bash setup_data.sh`. |
| - **Sync eval media** (original oops videos, random-shift videos, extracted audio): pulled from `hasnat79/ual_bench`, `Rakancorle11/random_shift_video`, `Rakancorle11/extracted_audio` into `/opt/dlami/nvme/video_source/`. |
|
|
| ## Default paths (convention) |
|
|
| Scripts assume a fixed split on every machine: |
|
|
| | What | Where | |
| |------|--------| |
| | Benchmark videos, merged full models, sync `video_source/` (original + shifted + audio) | `/opt/dlami/nvme/...` | |
| | Eval outputs (`eval_results.jsonl`, `metrics.json`, …) | `/home/ubuntu/eval_results/videomme`, `.../lvbench`, `.../sync` | |
|
|
| Override with `--video-dir`, `--output-dir`, `--data-root` if your layout differs. |
|
|
| ## Requirements |
|
|
| - Strong GPU(s), ~200GB+ disk for benchmarks + merged weights |
| - vLLM: `--tp` must divide **20** (audio encoder heads); e.g. `--tp 4`, not 8 |
| - `setup_env.sh` uses CUDA 12.4 PyTorch wheels by default; override `CUDA_INDEX_URL` if needed |
|
|
| ## Notes |
|
|
| - Eval scripts **resume** from existing `eval_results.jsonl`. |
| - In-domain sync: use `--data-root` so paths are not tied to `/home/ubuntu/video_source`. |
|
|
