Release FineAudio-Judge LoRA adapter and model card

LICENSE

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README.md

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 ---
+base_model: Qwen/Qwen3-Omni-30B-A3B-Instruct
+library_name: peft
 license: apache-2.0
+pipeline_tag: audio-text-to-text
 ---
+
+# FineAudio-Judge
+
+FineAudio-Judge evaluates consistency between audio and text descriptions
+or audio-generation instructions through prompt-derived rubric questions.
+Given an audio sample and a rubric question, it predicts a yes/no answer.
+
+This repository releases a LoRA adapter obtained by supervised fine-tuning
+the Thinker language model of
+[Qwen3-Omni-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Instruct).
+The adapter must be loaded together with the base model.
+
+## Files
+
+- `adapter_config.json`: PEFT LoRA configuration.
+- `adapter_model.safetensors`: FineAudio-Judge LoRA adapter weights.
+
+## Training
+
+- **Base**: [Qwen3-Omni-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Instruct)
+- **Corpus**: 12,508 constructed audio–prompt pairs (11,820 training and 688 validation), with 278,199 rubric-level question–answer examples used for training
+- **Method**: LoRA supervised fine-tuning
+- **Training schedule**: 1 epoch
+- **Hardware**: 8 × NVIDIA A800 80GB GPUs
+- **Per-device batch size**: 1
+- **Gradient accumulation steps**: 8
+- **Learning rate**: 5e-5
+- **LoRA configuration**: rank 64, alpha 64, dropout 0.05
+- **LoRA target modules**: `q_proj`, `k_proj`, `v_proj`, and `o_proj`
+  in the Thinker language model
+
+## Usage
+
+The evaluation scripts are provided in the
+[FineAudio-Judge code repository](https://github.com/QwenAudio/FunResearch/tree/main/FineAudio-Judge).
+They use ms-swift's vLLM inference engine to load
+Qwen3-Omni-30B-A3B-Instruct together with the released LoRA adapter.
+
+Clone the repository and enter the FineAudio-Judge directory:
+
+```bash
+git clone https://github.com/QwenAudio/FunResearch.git
+cd FunResearch/FineAudio-Judge
+```
+
+Follow the setup instructions in the code repository's README to install
+the project and configure the inference environment. Run the evaluation
+commands below from the `FunResearch/FineAudio-Judge/` directory.
+
+Replace `/path/to/benchmark` with the downloaded benchmark repository
+root and `/path/to/adapter` with the directory containing the released
+adapter files.
+
+### Rubric-QA evaluation
+
+Each audio–rubric question pair is evaluated independently.
+
+```bash
+python -m judge.cli.reproduce_rubric_qa \
+  --dataset-root /path/to/benchmark \
+  --model Qwen/Qwen3-Omni-30B-A3B-Instruct \
+  --adapter /path/to/adapter \
+  --output outputs/rubric_qa.jsonl
+```
+
+### Human-preference evaluation
+
+Rubrics are evaluated jointly for each candidate audio, and the proportion
+of yes predictions forms its prompt–audio consistency score.
+
+```bash
+python -m judge.cli.reproduce_preference \
+  --dataset-root /path/to/benchmark \
+  --model Qwen/Qwen3-Omni-30B-A3B-Instruct \
+  --adapter /path/to/adapter \
+  --output outputs/preference.jsonl
+```
+
+## License
+
+The FineAudio-Judge LoRA adapter is released under the Apache License 2.0.
+See [LICENSE](LICENSE) for details.
+
+The adapter is fine-tuned from
+[Qwen3-Omni-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Instruct),
+which is also released under the
+[Apache License 2.0](https://github.com/QwenLM/Qwen3-Omni/blob/main/LICENSE).
+The base model weights are not included in this repository.
+
+Base model copyright: Copyright 2025 Alibaba Cloud.

adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3-Omni-30B-A3B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [],
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": "^(thinker\\.model(?=\\.).*\\.(k_proj|q_proj|v_proj|o_proj))$",
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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