datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ipda-judge-adaptation-grpo
IPDA Judge Adaptation GRPO Dataset
Training data for judge adaptation in competitive debate. Contains GRPO preference sets for adapting debate speech generation to different judge profiles.
Dataset Description
This dataset enables training LLMs to adapt their debate arguments based on judge characteristics:
Depth Adaptation: Adapting explanation complexity to judge expertise level (debate experience + domain knowledge)
Bias Adaptation: Adapting argument framing to judge… See the full description on the dataset page: https://huggingface.co/datasets/debaterhub/ipda-judge-adaptation-grpo.ipda-golden-samples
IPDA Golden Samples (2AR + 1AR)
Golden samples for fine-tuning debate models on affirmative rebuttal speeches in IPDA format.
Dataset Description
874 high-quality samples for SFT training:
447 2AR (Second Affirmative Rebuttal)
427 1AR (First Affirmative Rebuttal)
Dataset Sources
Source
Count
Description
iter2_group_c
832
High-scoring (>=0.75) samples from GRPO iteration 2
augmented_claude-opus-4.5
20
Augmented debates generated by Claude Opus 4.5… See the full description on the dataset page: https://huggingface.co/datasets/dgonier/ipda-golden-samples.ipda-2ar-golden-samples
IPDA Golden Samples (2AR + 1AR)
Golden samples for fine-tuning debate models on affirmative rebuttal speeches in IPDA format.
Dataset Description
422 high-quality samples for SFT training:
260 2AR (Second Affirmative Rebuttal)
162 1AR (First Affirmative Rebuttal)
Dataset Sources
Model
2AR
1AR
Total
Claude Opus 4.5
100
50
150
GPT-5.2
100
50
150
Claude Sonnet
10
10
20
Claude Haiku
9
9
18
Qwen-ft (debate model)
19
19
38
Qwen-base
16
18
34… See the full description on the dataset page: https://huggingface.co/datasets/dgonier/ipda-2ar-golden-samples.ipda-grpo-training-data
IPDA GRPO Training Data
Training data for GRPO (Group Relative Policy Optimization) on IPDA debate tasks.
Dataset Description
Contains scored debate speech samples used for GRPO training iterations. Each sample includes:
Input prompt (debate context)
Generated response (speech)
Rubric scores from debate judge
Log probabilities for policy optimization
Files
File
Description
Samples
group_c_grpo.parquet
Group C (warrant/clash) training data
~3K… See the full description on the dataset page: https://huggingface.co/datasets/dgonier/ipda-grpo-training-data.ipda-cx-training-data
IPDA Cross-Examination Training Dataset
Training data for cross-examination (CX) skills in competitive debate. This dataset teaches models to ask strategic questions and provide defensible answers during cross-examination.
Dataset Structure
Files
File
Description
Records
cx_preference_pairs.jsonl
ORPO preference pairs (cleaned, no truncation)
2,322
cx_exchanges_all.jsonl
Full CX exchange dataset
16,556
all_scenarios.jsonl
Debate scenarios for CX… See the full description on the dataset page: https://huggingface.co/datasets/debaterhub/ipda-cx-training-data.ipda-grpo-nc-branched-v2ipda-sentence-selection-data
IPDA Sentence Selection Training Dataset
Training data for sentence-level claim selection in competitive debate. This dataset teaches models to select the most impactful claims to address during rebuttal speeches.
Dataset Structure
Files
File
Size
Description
sentence_selection_dataset.json
23MB
Full sentence selection dataset
sentence_dpo_format_consistent.json
4.4MB
DPO preference pairs (consistent format)
sentence_sft_train_v2.json
13MB
SFT… See the full description on the dataset page: https://huggingface.co/datasets/debaterhub/ipda-sentence-selection-data.ipda-phase5-v2
IPDA Debate Training Data - Phase 5 Iteration V2
Training data for IPDA (International Public Debate Association) debate AI model.
Dataset Description
This dataset contains per-call training examples extracted from full debate simulations, with quality scores assigned by a DSPy-based evaluation pipeline.
Pipeline Overview
Full Debate Generation: Complete IPDA debates generated using a DSPy pipeline with:
Multi-hop research via Tavily API
Structured speech… See the full description on the dataset page: https://huggingface.co/datasets/debaterhub/ipda-phase5-v2.ipda-judge-adaptation-data
IPDA Judge Adaptation Training Dataset
Training data for judge adaptation in competitive debate. This dataset teaches models to adapt their debate output based on judge characteristics.
Dataset Structure
Files
File
Description
Pairs
depth_iter1_train.json
Depth adaptation iteration 1 (lay vs expert judges)
75
depth_iter2_train.json
Depth adaptation iteration 2 (different topics)
75
bias_train.json
Bias adaptation (ideological, procedural… See the full description on the dataset page: https://huggingface.co/datasets/debaterhub/ipda-judge-adaptation-data.ipda-iter2-synthesis-callsipda-targeted-sft-v2ipda-judge-adaptation-grpo
IPDA Judge Adaptation GRPO Dataset
Training data for judge adaptation in competitive debate. Contains GRPO preference sets for adapting debate speech generation to different judge profiles.
Dataset Description
This dataset enables training LLMs to adapt their debate arguments based on judge characteristics:
Depth Adaptation: Adapting explanation complexity to judge expertise level (debate experience + domain knowledge)
Bias Adaptation: Adapting argument framing to judge… See the full description on the dataset page: https://huggingface.co/datasets/dgonier/ipda-judge-adaptation-grpo.ipda_grpo_multi_trial_thinking_tactics
Debate Multi-Trial GRPO Test Data (with Thinking Frameworks)
TEST DATASET - Single debate for review before scaling.
Training data for offline GRPO (Group Relative Policy Optimization) on IPDA debate generation,
with integrated thinking framework injection.
What's New: Thinking Frameworks
Each prompt includes structured thinking instructions (mnemonics) that guide the model's reasoning:
Call Type
Mnemonic
Purpose
TACTIC_SELECT
JAM
Judge-Attack-Momentum Analysis… See the full description on the dataset page: https://huggingface.co/datasets/debaterhub/ipda_grpo_multi_trial_thinking_tactics.ipda-debate-sft-iter3ipda-grpo-dataset-iter3-feb-12
IPDA GRPO Dataset — Iteration 3 (Feb 12, 2026)
GRPO (Group Relative Policy Optimization) training dataset for IPDA (International Public Debate Association) debate speech generation.
Dataset Structure
2,988 unique prompts | 11,425 scored trials | Score avg: 0.700 (0-1 scale)
Each row represents a unique debate pipeline prompt with up to 6 trial responses:
Column
Description
prompt_hash
SHA256[:16] of prompt text
prompt
Full pipeline prompt
speech_type
AC… See the full description on the dataset page: https://huggingface.co/datasets/dgonier/ipda-grpo-dataset-iter3-feb-12.ipda-iter2-judge-callsipda-sft-iter3v2-enriched