Processed data from AutoTrain data processor ([2023-04-18 14:50 ]

README.md

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+---
+task_categories:
+- image-classification
+
+---
+# AutoTrain Dataset for project: fine-tune
+
+## Dataset Description
+
+This dataset has been automatically processed by AutoTrain for project fine-tune.
+
+### 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": "<382x256 RGB PIL image>",
+    "target": 17
+  },
+  {
+    "image": "<341x256 RGB PIL image>",
+    "target": 7
+  }
+]
+```
+
+### Dataset Fields
+
+The dataset has the following fields (also called "features"):
+
+```json
+{
+  "image": "Image(decode=True, id=None)",
+  "target": "ClassLabel(names=['apple', 'banana', 'cake', 'candy', 'carrot', 'cookie', 'doughnut', 'grape', 'hot dog', 'ice cream', 'juice', 'muffin', 'orange', 'pineapple', 'popcorn', 'pretzel', 'salad', 'strawberry', 'waffle', 'watermelon'], 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        | 5394 |
+| valid        | 1351 |

processed/dataset_dict.json

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

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processed/train/dataset_info.json

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+{
+  "citation": "",
+  "description": "AutoTrain generated dataset",
+  "features": {
+    "image": {
+      "_type": "Image"
+    },
+    "target": {
+      "names": [
+        "apple",
+        "banana",
+        "cake",
+        "candy",
+        "carrot",
+        "cookie",
+        "doughnut",
+        "grape",
+        "hot dog",
+        "ice cream",
+        "juice",
+        "muffin",
+        "orange",
+        "pineapple",
+        "popcorn",
+        "pretzel",
+        "salad",
+        "strawberry",
+        "waffle",
+        "watermelon"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 706649397,
+      "num_examples": 5394,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "data-00000-of-00002.arrow"
+    },
+    {
+      "filename": "data-00001-of-00002.arrow"
+    }
+  ],
+  "_fingerprint": "649beef7e374c5d0",
+  "_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": [
+        "apple",
+        "banana",
+        "cake",
+        "candy",
+        "carrot",
+        "cookie",
+        "doughnut",
+        "grape",
+        "hot dog",
+        "ice cream",
+        "juice",
+        "muffin",
+        "orange",
+        "pineapple",
+        "popcorn",
+        "pretzel",
+        "salad",
+        "strawberry",
+        "waffle",
+        "watermelon"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "valid": {
+      "name": "valid",
+      "num_bytes": 176537468,
+      "num_examples": 1351,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "data-00000-of-00001.arrow"
+    }
+  ],
+  "_fingerprint": "d0b8595a183200d0",
+  "_format_columns": [
+    "image",
+    "target"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_output_all_columns": false,
+  "_split": null
+}