Upload w0.04 GRPO best RSR adapter

README.md

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+---
+base_model: Qwen/Qwen2.5-Omni-7B
+library_name: peft
+pipeline_tag: automatic-speech-recognition
+tags:
+- qwen2.5-omni
+- lora
+- peft
+- grpo
+- speech-in-context-learning
+- automatic-speech-recognition
+---
+
+# Qwen2.5-Omni SICL GRPO Best
+
+This repository contains a PEFT LoRA adapter for `Qwen/Qwen2.5-Omni-7B`.
+It is the best currently selected Qwen GRPO checkpoint from the SICL-GRPO experiments, selected by RSR 3-shot WER.
+
+## Checkpoint
+
+- Source checkpoint: `checkpoint-600`
+- Training job: `18288799`
+- Recipe: `ctx_good_perf_bad_2k`, seed 42
+- Reward setting: ICE-sim soft reward weight `w=0.04`
+- Local source path at export time: `checkpoint/Qwen2.5-Omni-7B/lora_grpo_ctx_good_perf_bad_2k_s42_ctx0p6_wer0p1_ice_soft_w004/18288799/v0-20260516-181131/checkpoint-600`
+
+## Evaluation
+
+ASR results report corpus-level WER. Bounded WER caps each utterance contribution at `1.0` before aggregation.
+
+| Eval | Shot | Raw WER | Bounded WER | Accuracy |
+| --- | ---: | ---: | ---: | ---: |
+| RSR selected eval | 3 | 16.79% | 16.56% | |
+| RSR full eval | 0 | 29.15% | 28.73% | |
+| RSR full eval | 3 | 16.63% | 16.32% | |
+| MYST full eval | 0 | 16.95% | 16.94% | |
+| MYST full eval | 3 | 11.25% | 11.23% | |
+| MMAR full eval | 0 | | | 49.50% |
+| MMAR full eval | 3 | | | 56.40% |
+| MMAU full eval | 0 | | | 66.80% |
+| MMAU full eval | 3 | | | 72.80% |
+
+## Usage
+
+Load this adapter with PEFT on top of `Qwen/Qwen2.5-Omni-7B` using the same inference stack as the SICL-GRPO experiments.
+
+```python
+from peft import PeftModel
+from transformers import Qwen2_5OmniForConditionalGeneration, Qwen2_5OmniProcessor
+
+base = Qwen2_5OmniForConditionalGeneration.from_pretrained(
+    "Qwen/Qwen2.5-Omni-7B",
+    device_map="auto",
+    trust_remote_code=True,
+)
+model = PeftModel.from_pretrained(base, "MagicLuke/qwen25omni-sicl-grpo-best")
+processor = Qwen2_5OmniProcessor.from_pretrained(
+    "Qwen/Qwen2.5-Omni-7B",
+    trust_remote_code=True,
+)
+```
+
+For audio inference, use the project inference scripts and message formatting for Qwen2.5-Omni.
+
+## Files
+
+This upload is adapter-only. It intentionally excludes optimizer, scheduler, RNG, and trainer state.

adapter_config.json

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+  "alpha_pattern": {},
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+  "base_model_name_or_path": "Qwen/Qwen2.5-Omni-7B",
+  "bias": "none",
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+  "ensure_weight_tying": false,
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+  "lora_bias": false,
+  "lora_dropout": 0.05,
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+  "megatron_core": "megatron.core",
+  "modules_to_save": [],
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
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+  "target_modules": "^(thinker\\.model(?=\\.).*\\.(o_proj|up_proj|gate_proj|down_proj|v_proj|k_proj|q_proj))$",
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+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 40425344

additional_config.json

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args.json

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