遇见数据集

reasoning-degeneration-dev/wmc-sft-warmup-traces-v1

收藏
Hugging Face2026-03-22 更新2026-03-29 收录
官方服务:

资源简介:

--- license: mit tags: - world-model-curiosity - sft-warmup - traces --- # wmc-sft-warmup-traces-v1 SFT warmup traces formatted for agg_visualizer Model Trace tab. Browse baseline vs CPB responses side by side. ## Dataset Info - **Rows**: 2400 - **Columns**: 7 ## Columns | Column | Type | Description | |--------|------|-------------| | condition | Value('string') | baseline or cpb | | question | Value('string') | Countdown problem (user prompt) | | system_prompt | Value('string') | System prompt for this condition | | response | Value('string') | Full assistant response including <think> block | | correct | Value('bool') | Whether the model solved correctly | | confidence | Value('float64') | Annotated confidence (CPB only) | | difficulty | Value('string') | easy/medium/hard | ## Generation Parameters ```json { "script_name": "generate_sft_data.py", "model": "Qwen/Qwen3-1.7B", "description": "SFT warmup traces formatted for agg_visualizer Model Trace tab. Browse baseline vs CPB responses side by side.", "hyperparameters": {}, "input_datasets": [] } ``` ## Experiment Documentation For complete experiment details, see [https://github.com/Zayne-sprague/SC-Research-Notes/tree/main/experiments/world-model-curiosity](https://github.com/Zayne-sprague/SC-Research-Notes/tree/main/experiments/world-model-curiosity) ## Usage ```python from datasets import load_dataset dataset = load_dataset("reasoning-degeneration-dev/wmc-sft-warmup-traces-v1", split="train") print(f"Loaded {len(dataset)} rows") ``` --- *This dataset is tracked in [reasoning-degeneration-dev/PROJECT-MANIFEST](https://huggingface.co/datasets/reasoning-degeneration-dev/PROJECT-MANIFEST)*

二维码
社区交流群
二维码
科研交流群
商业服务