diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7fbc979206fef95642f71d3aa275e46a819a21be --- /dev/null +++ b/README.md @@ -0,0 +1,101 @@ +# Humanizer-5M + +Version: 2.0.0 + +Humanizer-5M is a synthetic conversational adaptation dataset. + +The central objective is not simply to rewrite text to sound casual. + +Each example models: + +1. what the user explicitly asks, +2. what the user may implicitly need, +3. the user's conversational signals, +4. the appropriate response calibration, +5. the final response, +6. quality and stability metrics. + +The dataset specifically teaches proportional adaptation. + +High user energy does not automatically mean high hype. +Frustration does not automatically mean excessive empathy. +Casual language does not automatically require slang. +Emojis are used only when contextually appropriate. + +The dataset also contains hard negatives representing responses +that are grammatically correct but poorly calibrated. + +## Dataset size + +Total: 5,000,000 + +Train: 4,750,000 +Validation: 125,000 +Test: 125,000 + +Shard size: 100,000 + +## Core dimensions + +The dataset includes explicit calibration dimensions for: + +- energy +- hype +- empathy +- warmth +- formality +- directness +- verbosity +- humor +- emoji usage +- technicality +- confidence +- urgency + +## Quality metrics + +Examples also contain: + +- naturalness +- human_likeness_proxy +- context_fit +- emotional_fit +- hype_fit +- empathy_fit +- emoji_fit +- verbosity_fit +- directness_fit +- formality_fit +- humor_fit +- technicality_fit +- consistency +- emotional_stability +- overreaction_penalty +- forced_human_penalty +- generic_ai_penalty +- repetition_penalty +- emoji_overuse_penalty +- hype_without_reason_penalty +- tone_jump_penalty +- overall_quality + +## Hard negatives + +The dataset includes deliberately miscalibrated candidate responses. + +Examples include: + +- unnecessary hype +- forced empathy +- emoji overuse +- excessive verbosity +- generic assistant phrasing +- abrupt tone changes + +## Important + +Metrics are synthetic training labels and calibration signals. +They are not empirical measurements of whether a response was +written by a human. + +The dataset does not contain private conversations. diff --git a/dataset_card.md b/dataset_card.md new file mode 100644 index 0000000000000000000000000000000000000000..e62893429c955017059aa4c3d1bd92fe9cea7ca8 --- /dev/null +++ b/dataset_card.md @@ -0,0 +1,57 @@ +--- +language: +- fr +tags: +- conversational +- dialogue +- instruction-tuning +- tone-adaptation +- empathy +- style +- synthetic +size_categories: +- 1M