autotrain-data-processor commited on
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Processed data from AutoTrain data processor ([2023-09-21 23:19 ]

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README.md ADDED
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+ ---
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+ task_categories:
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+ - image-classification
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+
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+ ---
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+ # AutoTrain Dataset for project: vit-skin-derna
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+
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+ ## Dataset Description
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+
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+ This dataset has been automatically processed by AutoTrain for project vit-skin-derna.
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+
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+ ### Languages
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+
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+ The BCP-47 code for the dataset's language is unk.
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ A sample from this dataset looks as follows:
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+
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+ ```json
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+ [
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+ {
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+ "image": "<32x32 RGB PIL image>",
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+ "target": 4
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+ },
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+ {
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+ "image": "<32x32 RGB PIL image>",
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+ "target": 8
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+ }
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+ ]
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+ ```
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+
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+ ### Dataset Fields
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+
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+ The dataset has the following fields (also called "features"):
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+
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+ ```json
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+ {
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+ "image": "Image(decode=True, id=None)",
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+ "target": "ClassLabel(names=['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck'], id=None)"
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+ }
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+ ```
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+
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+ ### Dataset Splits
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+
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+ This dataset is split into a train and validation split. The split sizes are as follow:
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+
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+ | Split name | Num samples |
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+ | ------------ | ------------------- |
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+ | train | 40000 |
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+ | valid | 10000 |
processed/dataset_dict.json ADDED
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+ {"splits": ["train", "valid"]}
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+ {
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+ "citation": "",
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+ "description": "AutoTrain generated dataset",
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+ "features": {
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+ "image": {
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+ "_type": "Image"
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+ },
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+ "target": {
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+ "names": [
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+ "airplane",
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+ "automobile",
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+ "bird",
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+ "cat",
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+ "deer",
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+ "dog",
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+ "frog",
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+ "horse",
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+ "ship",
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+ "truck"
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+ ],
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+ "_type": "ClassLabel"
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+ }
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+ },
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+ "splits": {
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+ "num_examples": 40000,
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+ "dataset_name": null
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+ }
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+ }
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+ }
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+ "automobile",
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+ "bird",
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+ "cat",
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+ "deer",
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+ "dog",
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+ "frog",
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+ "horse",
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+ "ship",
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+ "truck"
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+ "_type": "ClassLabel"
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+ "num_examples": 10000,
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+ }
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