Datasets:

YangyiH
/

qwen3-4b-teacher-rollouts-76k-nonthinking

pretty_name: Qwen3-4B Teacher Rollouts 76K Non-Thinking
language:
  - en
task_categories:
  - text-generation
tags:
  - reasoning
  - knowledge-distillation
  - teacher-rollout
  - qwen3
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Qwen3-4B Teacher Rollouts 76K Non-Thinking

This dataset contains 76,800 fixed teacher trajectories generated for a prompt-aligned reproduction study of on-policy distillation with Qwen3-1.7B. It is an independent research artifact, not an official release from the model or paper authors.

Models and generation

Teacher: Qwen/Qwen3-4B-Instruct-2507
Tokenizer/chat template: Qwen/Qwen3-1.7B
Mode: non-thinking (enable_thinking=False)
Temperature: 0.7
Top-p: 1.0
Top-k: 0
Maximum prompt length: 4,096 tokens
Maximum completion length: 8,192 tokens
Seed for row i: 42 + i

Prompts were passed to the vLLM completions API as exact token IDs with no additional special tokens. Returned token IDs and special tokens are retained.

Statistics

Statistic	Value
Rows	76,800
Prompt tokens	21,596,089
Completion tokens	264,338,320
Total stored tokens	285,934,409
Mean completion length	3,441.91
Completions reaching 8,192 tokens	10,974 (14.29%)

The first 25,600 trajectories exactly reuse the earlier 100-step teacher bank. The remaining 51,200 rows extend the same seed-42 prompt permutation without an epoch wrap.

Fields

input_ids: concatenated prompt and completion token IDs
labels: -100 over prompt tokens and completion token IDs thereafter
prompt_ids, completion_ids: separate exact token sequences
messages: original conversation plus decoded teacher assistant response
domain: math, science, or code
source_dataset, source_config, source_split, source_shard, source_id: upstream provenance
prompt_sha256: hash of the source prompt
source_row_index, unified_order_index: source and rollout schedule indices
finish_reason, generation_seed: generation metadata

Integrity

Prompt order SHA-256: c1cc096fa94f82bf44457673b112039f604aaba19711a850f368514da6d7429d
Completion IDs SHA-256: a3c5ae8551b23025bb57d6d60a011ef7e156d034d0853656dbb33d29b064127b

The repository includes the full generation manifest. A post-generation audit found zero prompt-identity mismatches, and the prompt-token hash matches a fresh application of the documented Qwen non-thinking chat template.

Usage

from datasets import load_dataset

dataset = load_dataset(
    "YangyiH/qwen3-4b-teacher-rollouts-76k-nonthinking",
    split="train",
)

Source data and licensing

Prompts originate from the NVIDIA OpenMathReasoning, OpenScienceReasoning-2, and OpenCodeReasoning datasets. This repository does not assert a new blanket license over upstream prompt content. Users should review and comply with the source datasets' licenses, terms, and attribution requirements, as well as the Qwen model license.

Limitations

The source mixture intentionally retains duplicate prompts inherited from the upstream datasets.
No additional quality, difficulty, benchmark-contamination, or safety filtering was applied.
14.29% of completions reached the configured 8,192-token cap and may be truncated rather than naturally terminated.
Generated responses can contain errors or undesirable content inherited from the model and source prompts.