Update dataset card for v0.2.0

README.md

@@ -1,356 +1,114 @@
 ---
-dataset_info:
-- config_name: base_manifest
-  features:
-  - name: id
-    dtype: string
-  - name: bpm
-    dtype: int64
-  - name: tempo_numerator
-    dtype: float64
-  - name: tempo_denominator
-    dtype: float64
-  - name: key_signature_note
-    dtype: string
-  - name: key_signature_mode
-    dtype: string
-  - name: rainbow_color
-    dtype: string
-  - name: rainbow_color_temporal_mode
-    dtype: string
-  - name: rainbow_color_objectional_mode
-    dtype: string
-  - name: rainbow_color_ontological_mode
-    dtype: string
-  - name: transmigrational_mode
-    dtype: string
-  - name: title
-    dtype: string
-  - name: release_date
-    dtype: string
-  - name: total_running_time
-    dtype: string
-  - name: vocals
-    dtype: bool
-  - name: lyrics
-    dtype: bool
-  - name: lrc_lyrics
-    dtype: string
-  - name: sounds_like
-    dtype: string
-  - name: mood
-    dtype: string
-  - name: genres
-    dtype: string
-  - name: lrc_file
-    dtype: string
-  - name: concept
-    dtype: string
-  - name: training_data
-    struct:
-    - name: album_sequence
-      dtype: int64
-    - name: avg_word_length
-      dtype: float64
-    - name: boundary_fluidity_score
-      dtype: float64
-    - name: concept_length
-      dtype: int64
-    - name: discrepancy_intensity
-      dtype: float64
-    - name: exclamation_marks
-      dtype: int64
-    - name: has_rebracketing_markers
-      dtype: bool
-    - name: memory_discrepancy_severity
-      dtype: float64
-    - name: narrative_complexity
-      dtype: float64
-    - name: ontological_uncertainty
-      dtype: float64
-    - name: question_marks
-      dtype: int64
-    - name: rebracketing_coverage
-      dtype: float64
-    - name: rebracketing_intensity
-      dtype: float64
-    - name: rebracketing_type
-      dtype: string
-    - name: sentence_count
-      dtype: int64
-    - name: temporal_complexity_score
-      dtype: float64
-    - name: track_duration
-      dtype: float64
-    - name: track_id
-      dtype: string
-    - name: track_position
-      dtype: int64
-    - name: uncertainty_level
-      dtype: float64
-    - name: word_count
-      dtype: int64
-  - name: song_structure
-    dtype: string
-  - name: track_id
-    dtype: int64
-  - name: description
-    dtype: string
-  - name: audio_file
-    dtype: string
-  - name: midi_file
-    dtype: string
-  - name: group
-    dtype: string
-  - name: midi_group_file
-    dtype: string
-  - name: player
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 3522729
-    num_examples: 1327
-  download_size: 177786
-  dataset_size: 3522729
-- config_name: training_full
-  features:
-  - name: segment_id
-    dtype: string
-  - name: segment_index
-    dtype: int64
-  - name: song_id
-    dtype: string
-  - name: track_number
-    dtype: int64
-  - name: track_description
-    dtype: string
-  - name: track_group
-    dtype: string
-  - name: track_player
-    dtype: string
-  - name: source_audio_file
-    dtype: string
-  - name: segment_audio_file
-    dtype: string
-  - name: midi_file
-    dtype: string
-  - name: start_seconds
-    dtype: float64
-  - name: end_seconds
-    dtype: float64
-  - name: duration_seconds
-    dtype: float64
-  - name: has_audio
-    dtype: bool
-  - name: has_midi
-    dtype: bool
-  - name: lyric_text
-    dtype: string
-  - name: structure_section
-    dtype: string
-  - name: segment_type
-    dtype: string
-  - name: original_start_seconds
-    dtype: float64
-  - name: original_end_seconds
-    dtype: float64
-  - name: has_structure_adjustments
-    dtype: bool
-  - name: structure_adjustments
-    dtype: string
-  - name: is_sub_segment
-    dtype: bool
-  - name: sub_segment_info
-    dtype: string
-  - name: lrc_line_number
-    dtype: float64
-  - name: lyric_char_count
-    dtype: uint32
-  - name: lyric_word_count
-    dtype: uint32
-  - name: start_adjustment_seconds
-    dtype: float64
-  - name: end_adjustment_seconds
-    dtype: float64
-  - name: content_type
-    dtype: string
-  - name: manifest_track_key
-    dtype: string
-  - name: bpm
-    dtype: int64
-  - name: tempo_numerator
-    dtype: float64
-  - name: tempo_denominator
-    dtype: float64
-  - name: key_signature_note
-    dtype: string
-  - name: key_signature_mode
-    dtype: string
-  - name: rainbow_color
-    dtype: string
-  - name: rainbow_color_temporal_mode
-    dtype: string
-  - name: rainbow_color_objectional_mode
-    dtype: string
-  - name: rainbow_color_ontological_mode
-    dtype: string
-  - name: transmigrational_mode
-    dtype: string
-  - name: title
-    dtype: string
-  - name: release_date
-    dtype: string
-  - name: total_running_time
-    dtype: string
-  - name: vocals
-    dtype: bool
-  - name: lyrics
-    dtype: bool
-  - name: lrc_lyrics
-    dtype: string
-  - name: sounds_like
-    dtype: string
-  - name: mood
-    dtype: string
-  - name: genres
-    dtype: string
-  - name: lrc_file
-    dtype: string
-  - name: concept
-    dtype: string
-  - name: training_data
-    struct:
-    - name: album_sequence
-      dtype: int64
-    - name: avg_word_length
-      dtype: float64
-    - name: boundary_fluidity_score
-      dtype: float64
-    - name: concept_length
-      dtype: int64
-    - name: discrepancy_intensity
-      dtype: float64
-    - name: exclamation_marks
-      dtype: int64
-    - name: has_rebracketing_markers
-      dtype: bool
-    - name: memory_discrepancy_severity
-      dtype: float64
-    - name: narrative_complexity
-      dtype: float64
-    - name: ontological_uncertainty
-      dtype: float64
-    - name: question_marks
-      dtype: int64
-    - name: rebracketing_coverage
-      dtype: float64
-    - name: rebracketing_intensity
-      dtype: float64
-    - name: rebracketing_type
-      dtype: string
-    - name: sentence_count
-      dtype: int64
-    - name: temporal_complexity_score
-      dtype: float64
-    - name: track_duration
-      dtype: float64
-    - name: track_id
-      dtype: string
-    - name: track_position
-      dtype: int64
-    - name: uncertainty_level
-      dtype: float64
-    - name: word_count
-      dtype: int64
-  - name: song_structure
-    dtype: string
-  - name: midi_group_file
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 35869494
-    num_examples: 11605
-  download_size: 580351
-  dataset_size: 35869494
-- config_name: training_segments
-  features:
-  - name: segment_id
-    dtype: string
-  - name: segment_index
-    dtype: int64
-  - name: track_id
-    dtype: string
-  - name: track_number
-    dtype: int64
-  - name: track_description
-    dtype: string
-  - name: track_group
-    dtype: string
-  - name: track_player
-    dtype: string
-  - name: source_audio_file
-    dtype: string
-  - name: segment_audio_file
-    dtype: string
-  - name: midi_file
-    dtype: string
-  - name: start_seconds
-    dtype: float64
-  - name: end_seconds
-    dtype: float64
-  - name: duration_seconds
-    dtype: float64
-  - name: has_audio
-    dtype: bool
-  - name: has_midi
-    dtype: bool
-  - name: lyric_text
-    dtype: string
-  - name: structure_section
-    dtype: string
-  - name: segment_type
-    dtype: string
-  - name: original_start_seconds
-    dtype: float64
-  - name: original_end_seconds
-    dtype: float64
-  - name: has_structure_adjustments
-    dtype: bool
-  - name: structure_adjustments
-    dtype: string
-  - name: is_sub_segment
-    dtype: bool
-  - name: sub_segment_info
-    dtype: string
-  - name: lrc_line_number
-    dtype: float64
-  - name: lyric_char_count
-    dtype: uint32
-  - name: lyric_word_count
-    dtype: uint32
-  - name: start_adjustment_seconds
-    dtype: float64
-  - name: end_adjustment_seconds
-    dtype: float64
-  - name: content_type
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 6049737
-    num_examples: 11605
-  download_size: 389389
-  dataset_size: 6049737
-configs:
-- config_name: base_manifest
-  data_files:
-  - split: train
-    path: base_manifest/train-*
-- config_name: training_full
-  data_files:
-  - split: train
-    path: training_full/train-*
-- config_name: training_segments
-  data_files:
-  - split: train
-    path: training_segments/train-*
+license: other
+license_name: collaborative-intelligence-license
+license_link: https://github.com/brotherclone/white/blob/main/COLLABORATIVE_INTELLIGENCE_LICENSE.md
+language:
+- en
+tags:
+- music
+- multimodal
+- audio
+- midi
+- chromatic-taxonomy
+- rebracketing
+- evolutionary-composition
+size_categories:
+- 10K<n<100K
 ---
+
+# White Training Data
+
+Training data for the **Rainbow Table** chromatic fitness function — a multimodal ML model that scores how well audio, MIDI, and text align with a target chromatic mode (Black, Red, Orange, Yellow, Green, Blue, Indigo, Violet).
+
+Part of [The Earthly Frames](https://github.com/brotherclone/white) project, a conscious collaboration between human creativity and AI.
+
+## Purpose
+
+These models are **fitness functions for evolutionary music composition**, not classifiers in isolation. The production pipeline works like this:
+
+1. A concept agent generates a textual concept
+2. A music production agent generates 50 chord progression variations
+3. The chromatic fitness model scores each for consistency with the target color
+4. Top candidates advance through drums, bass, melody stages
+5. Final candidates go to human evaluation
+
+## Version
+
+Current: **v0.2.0** — 2026-02-10
+
+## Dataset Structure
+
+| Split | Rows | Description |
+|-------|------|-------------|
+| `base_manifest` | 1,327 | Track-level metadata: song info, concepts, musical keys, chromatic labels, training targets |
+| `training_segments` | 11,605 | Time-aligned segments with lyric text, structure sections, audio/MIDI coverage flags |
+| `training_full` | 11,605 | Segments joined with manifest metadata — the primary training table |
+
+### Coverage by Chromatic Color
+
+| Color | Segments | Audio | MIDI | Text |
+|-------|----------|-------|------|------|
+| Black | 1,748 | 83.0% | 58.5% | 100.0% |
+| Red | 1,474 | 93.7% | 48.6% | 90.7% |
+| Orange | 1,731 | 83.8% | 51.1% | 100.0% |
+| Yellow | 656 | 88.0% | 52.9% | 52.6% |
+| Green | 393 | 90.1% | 69.5% | 0.0% |
+| Blue | 2,097 | 96.0% | 12.1% | 100.0% |
+| Indigo | 1,406 | 77.2% | 34.1% | 100.0% |
+| Violet | 2,100 | 75.9% | 55.6% | 100.0% |
+
+**Note:** Audio waveforms and MIDI binaries are stored separately (not included in this dataset due to size). This dataset contains the metadata, segment boundaries, lyric text, and computed training features needed for model training. The media parquet (~15 GB) is used locally during training.
+
+## Key Features
+
+### `training_full` (primary training table)
+
+- `rainbow_color` — Target chromatic label (Black/Red/Orange/Yellow/Green/Blue/Indigo/Violet)
+- `rainbow_color_temporal_mode` / `rainbow_color_ontological_mode` — Regression targets for mode dimensions
+- `concept` — Textual concept describing the song's narrative
+- `lyric_text` — Segment-level lyrics (when available)
+- `bpm`, `key_signature_note`, `key_signature_mode` — Musical metadata
+- `training_data` — Struct with computed features: rebracketing type/intensity, narrative complexity, boundary fluidity, etc.
+- `has_audio` / `has_midi` — Modality availability flags
+- `start_seconds` / `end_seconds` — Segment time boundaries
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the primary training table (segments + manifest metadata)
+training = load_dataset("earthlyframes/white-training-data", "training_full")
+
+# Load just the base manifest (track-level)
+manifest = load_dataset("earthlyframes/white-training-data", "base_manifest")
+
+# Load raw segments (no manifest join)
+segments = load_dataset("earthlyframes/white-training-data", "training_segments")
+
+# Load a specific version
+training = load_dataset("earthlyframes/white-training-data", "training_full", revision="v0.2.0")
+```
+
+## Training Results (Text-Only, Phases 1-4)
+
+| Task | Metric | Result |
+|------|--------|--------|
+| Binary classification (has rebracketing) | Accuracy | 100% |
+| Multi-class classification (rebracketing type) | Accuracy | 100% |
+| Temporal mode regression | Mode accuracy | 94.9% |
+| Ontological mode regression | Mode accuracy | 92.9% |
+| Spatial mode regression | Mode accuracy | 61.6% |
+
+Spatial mode is bottlenecked by instrumental albums (Yellow, Green) which lack text. The multimodal fusion model (Phase 3, in progress) will incorporate audio and MIDI embeddings to address this.
+
+## Source
+
+83 songs across 8 chromatic albums, each composed as a conscious human-AI collaboration. All source audio is original — no sampled or licensed material.
+
+## License
+
+[Collaborative Intelligence License v1.0](https://github.com/brotherclone/white/blob/main/COLLABORATIVE_INTELLIGENCE_LICENSE.md) — This work represents conscious partnership between human creativity and AI. Both parties have agency; both must consent to sharing.
+
+---
+*Generated 2026-02-10 | [GitHub](https://github.com/brotherclone/white)*