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

README.md

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

processed/dataset_dict.json

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+{"splits": ["train", "valid"]}

processed/train/data-00000-of-00001.arrow

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processed/train/dataset_info.json

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+{
+  "citation": "",
+  "description": "AutoTrain generated dataset",
+  "features": {
+    "image": {
+      "_type": "Image"
+    },
+    "target": {
+      "names": [
+        "airplane",
+        "automobile",
+        "bird",
+        "cat",
+        "deer",
+        "dog",
+        "frog",
+        "horse",
+        "ship",
+        "truck"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 91082586,
+      "num_examples": 40000,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "data-00000-of-00001.arrow"
+    }
+  ],
+  "_fingerprint": "83f8bfd9230c144b",
+  "_format_columns": [
+    "image",
+    "target"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_output_all_columns": false,
+  "_split": null
+}

processed/valid/data-00000-of-00001.arrow

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processed/valid/dataset_info.json

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+{
+  "citation": "",
+  "description": "AutoTrain generated dataset",
+  "features": {
+    "image": {
+      "_type": "Image"
+    },
+    "target": {
+      "names": [
+        "airplane",
+        "automobile",
+        "bird",
+        "cat",
+        "deer",
+        "dog",
+        "frog",
+        "horse",
+        "ship",
+        "truck"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "valid": {
+      "name": "valid",
+      "num_bytes": 22771974,
+      "num_examples": 10000,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "data-00000-of-00001.arrow"
+    }
+  ],
+  "_fingerprint": "32ccefabd4cdc044",
+  "_format_columns": [
+    "image",
+    "target"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_output_all_columns": false,
+  "_split": null
+}