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README.md

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+---
+license: other
+tags: [meta-reasoning, qwen3_5, condgen]
+---
+
+# MR_midtrain_9B_v5_condgen
+
+This is the **final step-4128 checkpoint**, not the best-validation checkpoint,
+of a six-epoch V5 supervised midtraining run from the stock Qwen3.5-9B weights.
+The model uses the `Qwen3_5ForConditionalGeneration` architecture and is
+published with the vision tower in the flat `model.visual.*` key layout expected
+by verl's Megatron bridge. The export changes only the names of 333 vision
+tensors from `model.language_model.visual.*`; their values are not modified.
+The vision tower is carried from the base model and was not a target of the
+text-only SFT run.
+
+## Training data and format
+
+The training split contained 88,115 examples: 49,188 exploration (E), 29,450
+meta-reasoning (MR), 6,477 final-answer (FA), and 3,000 termination traces.
+It was derived from `HerrHruby/MR_midtrain_V5_sft` with additional termination
+traces sampled from existing frontiers. The unchanged validation split had 258
+examples. Training used the V4 verl/FSDP recipe with a 65,536-token maximum
+training length and the V5 attribution-aware tokenizer.
+
+FA training targets retain the FA chain of thought through `</think>`, then emit
+`<attribution>...</attribution>` before the final answer or proof. The tokenizer
+preserves the V4 `<direction>`, `</direction>`, `<summary>`, and `</summary>`
+tokens (IDs 248077–248080) and adds `<attribution>` and `</attribution>` as
+atomic special tokens (IDs 248081–248082). The model's embedding size is
+unchanged.
+
+The final checkpoint's validation loss was 0.642673. The lowest validation
+loss in the run was 0.642636 at step 2700, but that checkpoint is **not** the
+one published here. These losses are training diagnostics, not a downstream
+benchmark evaluation.
+
+## Compatibility
+
+The flat vision-tower key layout matches the published
+[`MR_midtrain_9B_v4_condgen`](https://huggingface.co/HerrHruby/MR_midtrain_9B_v4_condgen)
+layout and is intended for verl/Megatron loading. It also retains the full
+conditional-generation architecture for Transformers and vLLM. For text-only
+vLLM serving, disable image and video inputs (for example with
+`--limit-mm-per-prompt '{"image":0,"video":0}'`).
+
+The export process first merges the final verl FSDP model shards into a
+Hugging Face safetensors checkpoint, then re-keys the 333 vision tensors.
+Optimizer and dataloader states are not part of this inference/RL-init export.