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README.md

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+---
+dataset_info:
+- config_name: all
+  features:
+  - name: audio
+    dtype:
+      audio:
+        decode: false
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': NSW_3
+          '1': NSW_2
+          '2': NSW_1
+          '3': SW_Dana
+          '4': SW_Luna
+          '5': SW_Nana
+          '6': SW_Neo
+          '7': SW_Nikita
+          '8': SW_Shy
+          '9': SW_Yosefa
+  - name: name
+    dtype: string
+  - name: onset
+    dtype: float32
+  - name: offset
+    dtype: float32
+  - name: duration
+    dtype: float32
+  - name: recording_duration
+    dtype: float32
+  - name: whistle_type
+    dtype: int64
+  - name: whistle_name
+    dtype: string
+  - name: f0_time
+    sequence: float32
+  - name: f0_hz
+    sequence: float32
+  - name: f0_conf
+    sequence: float32
+  - name: f0_ok
+    dtype: bool
+  - name: f0_bad_reason
+    dtype: string
+  - name: f0_spectrogram
+    dtype: image
+  splits:
+  - name: train
+    num_examples: 5848
+  - name: validation
+    num_examples: 1253
+  - name: test
+    num_examples: 1253
+- config_name: all-review-sample
+  features:
+  - name: audio
+    dtype:
+      audio:
+        decode: false
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': NSW_3
+          '1': NSW_2
+          '2': NSW_1
+          '3': SW_Dana
+          '4': SW_Luna
+          '5': SW_Nana
+          '6': SW_Neo
+          '7': SW_Nikita
+          '8': SW_Shy
+          '9': SW_Yosefa
+  - name: name
+    dtype: string
+  - name: onset
+    dtype: float32
+  - name: offset
+    dtype: float32
+  - name: duration
+    dtype: float32
+  - name: recording_duration
+    dtype: float32
+  - name: whistle_type
+    dtype: int64
+  - name: whistle_name
+    dtype: string
+  - name: f0_time
+    sequence: float32
+  - name: f0_hz
+    sequence: float32
+  - name: f0_conf
+    sequence: float32
+  - name: f0_ok
+    dtype: bool
+  - name: f0_bad_reason
+    dtype: string
+  - name: f0_spectrogram
+    dtype: image
+  splits:
+  - name: train
+    num_examples: 336
+  - name: validation
+    num_examples: 72
+  - name: test
+    num_examples: 72
+- config_name: balanced
+  features:
+  - name: audio
+    dtype:
+      audio:
+        decode: false
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': NSW_1
+          '1': SW_Luna
+          '2': SW_Nana
+          '3': SW_Neo
+          '4': SW_Nikita
+          '5': SW_Yosefa
+  - name: name
+    dtype: string
+  - name: onset
+    dtype: float32
+  - name: offset
+    dtype: float32
+  - name: duration
+    dtype: float32
+  - name: recording_duration
+    dtype: float32
+  - name: whistle_type
+    dtype: int64
+  - name: whistle_name
+    dtype: string
+  - name: f0_time
+    sequence: float32
+  - name: f0_hz
+    sequence: float32
+  - name: f0_conf
+    sequence: float32
+  - name: f0_ok
+    dtype: bool
+  - name: f0_bad_reason
+    dtype: string
+  - name: f0_spectrogram
+    dtype: image
+  splits:
+  - name: train
+    num_examples: 2100
+  - name: validation
+    num_examples: 450
+  - name: test
+    num_examples: 450
+- config_name: balanced-review-sample
+  features:
+  - name: audio
+    dtype:
+      audio:
+        decode: false
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': NSW_1
+          '1': SW_Luna
+          '2': SW_Nana
+          '3': SW_Neo
+          '4': SW_Nikita
+          '5': SW_Yosefa
+  - name: name
+    dtype: string
+  - name: onset
+    dtype: float32
+  - name: offset
+    dtype: float32
+  - name: duration
+    dtype: float32
+  - name: recording_duration
+    dtype: float32
+  - name: whistle_type
+    dtype: int64
+  - name: whistle_name
+    dtype: string
+  - name: f0_time
+    sequence: float32
+  - name: f0_hz
+    sequence: float32
+  - name: f0_conf
+    sequence: float32
+  - name: f0_ok
+    dtype: bool
+  - name: f0_bad_reason
+    dtype: string
+  - name: f0_spectrogram
+    dtype: image
+  splits:
+  - name: train
+    num_examples: 336
+  - name: validation
+    num_examples: 72
+  - name: test
+    num_examples: 72
+- config_name: unbalanced
+  features:
+  - name: audio
+    dtype:
+      audio:
+        decode: false
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': NSW_3
+          '1': NSW_2
+          '2': NSW_1
+          '3': SW_Dana
+          '4': SW_Luna
+          '5': SW_Nana
+          '6': SW_Neo
+          '7': SW_Nikita
+          '8': SW_Shy
+          '9': SW_Yosefa
+  - name: name
+    dtype: string
+  - name: onset
+    dtype: float32
+  - name: offset
+    dtype: float32
+  - name: duration
+    dtype: float32
+  - name: recording_duration
+    dtype: float32
+  - name: whistle_type
+    dtype: int64
+  - name: whistle_name
+    dtype: string
+  - name: f0_time
+    sequence: float32
+  - name: f0_hz
+    sequence: float32
+  - name: f0_conf
+    sequence: float32
+  - name: f0_ok
+    dtype: bool
+  - name: f0_bad_reason
+    dtype: string
+  - name: f0_spectrogram
+    dtype: image
+  splits:
+  - name: train
+    num_examples: 2442
+  - name: validation
+    num_examples: 523
+  - name: test
+    num_examples: 523
+- config_name: unbalanced-review-sample
+  features:
+  - name: audio
+    dtype:
+      audio:
+        decode: false
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': NSW_3
+          '1': NSW_2
+          '2': NSW_1
+          '3': SW_Dana
+          '4': SW_Luna
+          '5': SW_Nana
+          '6': SW_Neo
+          '7': SW_Nikita
+          '8': SW_Shy
+          '9': SW_Yosefa
+  - name: name
+    dtype: string
+  - name: onset
+    dtype: float32
+  - name: offset
+    dtype: float32
+  - name: duration
+    dtype: float32
+  - name: recording_duration
+    dtype: float32
+  - name: whistle_type
+    dtype: int64
+  - name: whistle_name
+    dtype: string
+  - name: f0_time
+    sequence: float32
+  - name: f0_hz
+    sequence: float32
+  - name: f0_conf
+    sequence: float32
+  - name: f0_ok
+    dtype: bool
+  - name: f0_bad_reason
+    dtype: string
+  - name: f0_spectrogram
+    dtype: image
+  splits:
+  - name: train
+    num_examples: 336
+  - name: validation
+    num_examples: 72
+  - name: test
+    num_examples: 72
+task_categories:
+- audio-classification
+tags:
+- dolphin
+- bioacoustics
+- whistle-classification
+- audio
+- f0
+- spectrogram
+configs:
+- config_name: all
+  data_files:
+  - split: train
+    path: all/train-*
+  - split: validation
+    path: all/validation-*
+  - split: test
+    path: all/test-*
+- config_name: all-review-sample
+  data_files:
+  - split: train
+    path: all-review-sample/train-*
+  - split: validation
+    path: all-review-sample/validation-*
+  - split: test
+    path: all-review-sample/test-*
+- config_name: balanced
+  data_files:
+  - split: train
+    path: balanced/train-*
+  - split: validation
+    path: balanced/validation-*
+  - split: test
+    path: balanced/test-*
+- config_name: balanced-review-sample
+  data_files:
+  - split: train
+    path: balanced-review-sample/train-*
+  - split: validation
+    path: balanced-review-sample/validation-*
+  - split: test
+    path: balanced-review-sample/test-*
+- config_name: unbalanced
+  data_files:
+  - split: train
+    path: unbalanced/train-*
+  - split: validation
+    path: unbalanced/validation-*
+  - split: test
+    path: unbalanced/test-*
+- config_name: unbalanced-review-sample
+  data_files:
+  - split: train
+    path: unbalanced-review-sample/train-*
+  - split: validation
+    path: unbalanced-review-sample/validation-*
+  - split: test
+    path: unbalanced-review-sample/test-*
+---
+
+# OpenWhistle Classification Finetuning Dataset
+
+`OpenWhistle/OpenWhistle-Classification-Finetuning` is the public
+classification finetuning dataset used for dolphin whistle identity
+classification. It contains short whistle clips, whistle-level metadata,
+fundamental-frequency tracks, rendered F0 spectrograms, and integer class
+labels.
+
+The main reviewer-facing subset is the balanced `balanced` config. It contains
+six classes:
+
+- `NSW_1` (`label=0`)
+- `SW_Luna` (`label=1`)
+- `SW_Nana` (`label=2`)
+- `SW_Neo` (`label=3`)
+- `SW_Nikita` (`label=4`)
+- `SW_Yosefa` (`label=5`)
+
+The full dataset is split by recording session, so no session appears in more
+than one of `train`, `validation`, or `test`. Smaller deterministic review
+configs are also provided so reviewers can inspect representative examples
+quickly without downloading the complete data first.
+
+## Dataset Contents
+
+- Hugging Face repo: `OpenWhistle/OpenWhistle-Classification-Finetuning`
+- Main balanced config: `balanced`
+- Reviewer convenience config: `balanced-review-sample`
+- Public columns: `audio`, `label`, `name`, `onset`, `offset`, `duration`,
+  `recording_duration`, `whistle_type`, `whistle_name`, `f0_time`, `f0_hz`,
+  `f0_conf`, `f0_ok`, `f0_bad_reason`, `f0_spectrogram`
+
+## Balanced Dataset Splits
+
+| Split | Rows | NSW_1 | SW_Luna | SW_Nana | SW_Neo | SW_Nikita | SW_Yosefa | Sessions |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: | ---: | ---: |
+| `train` | 2,100 | 350 | 350 | 350 | 350 | 350 | 350 | 161 |
+| `validation` | 450 | 75 | 75 | 75 | 75 | 75 | 75 | 54 |
+| `test` | 450 | 75 | 75 | 75 | 75 | 75 | 75 | 37 |
+| **Total** | **3,000** | **500** | **500** | **500** | **500** | **500** | **500** | **252** |
+
+The split assignment was generated with seed `42` and exact class balancing.
+Session leakage checks found no overlap between any pair of splits.
+
+## Available Subsets
+
+The repository provides three full classification subsets and their smaller
+review counterparts:
+
+| Subset/config | Rows | Classes | Sessions | Purpose |
+| --- | ---: | ---: | ---: | --- |
+| `balanced` | 3,000 | 6 | 252 | Main balanced six-class finetuning dataset |
+| `unbalanced` | 3,488 | 10 | 258 | Ten-class finetuning dataset with capped rare classes |
+| `all` | 8,354 | 10 | 261 | Ten-class dataset preserving the full available class distribution |
+| `balanced-review-sample` | 480 | 6 | Same source split design | Small reviewer sample from `balanced` |
+| `unbalanced-review-sample` | 480 | 10 | Same source split design | Small reviewer sample from `unbalanced` |
+| `all-review-sample` | 480 | 10 | Same source split design | Small reviewer sample from `all` |
+
+The ten-class subsets use the following labels:
+
+- `NSW_3`
+- `NSW_2`
+- `NSW_1`
+- `SW_Dana`
+- `SW_Luna`
+- `SW_Nana`
+- `SW_Neo`
+- `SW_Nikita`
+- `SW_Shy`
+- `SW_Yosefa`
+
+The `balanced` subset keeps the six classes listed above and is the recommended
+starting point for reviewers and model finetuning. The `unbalanced` and `all`
+subsets expose the broader ten-class label space for additional analysis.
+
+## Review Samples
+
+Review samples are small deterministic subsets of the same public dataset. They
+were created only to make review and manual inspection easier. They are not a
+replacement for the full configs used for model development or reporting.
+
+### How The Review Samples Were Created
+
+All review samples were built after the session-disjoint train/validation/test
+splits were finalized. The review-sample scripts preserve the original split
+assignment: reviewer training examples come only from the original `train`
+split, reviewer validation examples only from `validation`, and reviewer test
+examples only from `test`.
+
+For `balanced-review-sample`, rows were sampled separately within each split and
+class. Each class group was shuffled deterministically with
+`numpy.default_rng(seed + split_index)` using seed `42`, then capped at 56 rows
+per class for `train` and 12 rows per class for both `validation` and `test`.
+This keeps the same 70/15/15 split ratio as the full `balanced` config while
+keeping every class equally represented.
+
+For `unbalanced-review-sample` and `all-review-sample`, the same deterministic
+shuffle was used, but the target rows were allocated proportionally to the
+source class distribution inside each split. This preserves the class imbalance
+of the larger source configs while keeping the review download small.
+
+### Review Sample Sizes
+
+| Config | Source config | Strategy | Train | Validation | Test | Total |
+| --- | --- | --- | ---: | ---: | ---: | ---: |
+| `balanced-review-sample` | `balanced` | Equal rows per class within each split | 336 | 72 | 72 | 480 |
+| `unbalanced-review-sample` | `unbalanced` | Proportional class distribution within each split | 336 | 72 | 72 | 480 |
+| `all-review-sample` | `all` | Proportional class distribution within each split | 336 | 72 | 72 | 480 |
+
+The reviewer-facing sample for the main balanced dataset is
+`balanced-review-sample`. The other review samples are included so each full
+subset has a matching small inspection subset.
+
+## Loading The Data
+
+```python
+from datasets import load_dataset
+
+full = load_dataset(
+    "OpenWhistle/OpenWhistle-Classification-Finetuning",
+    "balanced",
+)
+review = load_dataset(
+    "OpenWhistle/OpenWhistle-Classification-Finetuning",
+    "balanced-review-sample",
+)
+```
+
+Optional broader configs can be loaded by passing `"unbalanced"` or `"all"` as
+the second `load_dataset` argument. Their corresponding review configs are
+`"unbalanced-review-sample"` and `"all-review-sample"`.

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