---
license: other
language: [en]
tags: [midtraining, code, agentic, software-engineering, multi-agent]
task_categories: [text-generation]
---

# CooperData v3 — Midtraining Blend (Qwen3.5-9B cooperative SWE agents)

All-token **midtraining** mixture that bridges `Qwen/Qwen3.5-9B` (instruct) toward the cooperative
multi-agent SWE-coding SFT distribution. **One document per row** (`text`, tagged by `source`) — NOT
packed — so `trl.SFTTrainer(packing=False)` tokenizes per-doc and the Gated-DeltaNet recurrence
stays per-document. **~390M tokens.**

## Composition
| source | tokens | share | role |
|---|---|---|---|
| `web` | 210.0M | 54% | general |
| `math` | 55.0M | 14% | general |
| `instruct` | 25.0M | 6% | general |
| `coop` | 60.0M | 15% | bridge |
| `swe_smith` | 15.0M | 4% | bridge |
| `nebius` | 15.0M | 4% | bridge |
| `social` | 10.0M | 3% | bridge |

General **~74%** / bridge **~26%** (coop-dominant). Agentic/social sources are rendered with
the model's **real** chat template (so coop tool-calls become native `<tool_call>`/`<tool_response>`,
matching the `qwen3_coder` serving parser).

## Methodology
Grounded in ["Midtraining Bridges Pretraining and Posttraining Distributions" (2510.14865)](https://arxiv.org/abs/2510.14865):
specialized data is introduced *late* (a finished instruct model), so the conservative-weight finding
(high specialized weight late -> catastrophic forgetting) dictates a **general-dominant** mix. The
bridge is coop-dominant — near-domain agentic-coding on a coding model (low forgetting risk) and the
exact SFT target. Heavy agentic specialization is left to SFT.

## Usage (all-token, packing=False)
```python
from trl import SFTTrainer, SFTConfig
from datasets import load_dataset
ds = load_dataset("CooperBench/cooperdata-v3-midtrain-blend", split="train")
SFTTrainer(model="Qwen/Qwen3.5-9B", train_dataset=ds,
           args=SFTConfig(dataset_text_field="text", packing=False, max_length=8192))
```

## Build
`coopertrain/train/modal/datamix/` (sources + mixture + cleaning). Inherits the licenses of its
constituent datasets (Dolmino, mini-coder-trajs, OdysSim) + our coop trajectories.