Processed data from AutoTrain data processor ([2023-06-13 13:04 ]

README.md

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+---
+language:
+- en
+task_categories:
+- token-classification
+
+---
+# AutoTrain Dataset for project: aniaitokenclassification
+
+## Dataset Description
+
+This dataset has been automatically processed by AutoTrain for project aniaitokenclassification.
+
+### Languages
+
+The BCP-47 code for the dataset's language is en.
+
+## Dataset Structure
+
+### Data Instances
+
+A sample from this dataset looks as follows:
+
+```json
+[
+  {
+    "tokens": [
+      "I",
+      " booked",
+      "a",
+      " flight",
+      "to",
+      "London."
+    ],
+    "tags": [
+      4,
+      2,
+      2,
+      5,
+      2,
+      1
+    ]
+  },
+  {
+    "tokens": [
+      "Apple",
+      "Inc.",
+      "is",
+      "planning",
+      "to",
+      "open",
+      "a",
+      "new",
+      "store",
+      "in",
+      "Paris."
+    ],
+    "tags": [
+      3,
+      3,
+      2,
+      2,
+      2,
+      2,
+      2,
+      2,
+      2,
+      2,
+      1
+    ]
+  }
+]
+```
+
+### Dataset Fields
+
+The dataset has the following fields (also called "features"):
+
+```json
+{
+  "tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
+  "tags": "Sequence(feature=ClassLabel(names=['COMPANY', 'LOC', 'O', 'ORG', 'PER', 'THING'], id=None), length=-1, 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        | 23 |
+| valid        | 6 |

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": {
+    "tokens": {
+      "feature": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "_type": "Sequence"
+    },
+    "tags": {
+      "feature": {
+        "names": [
+          "COMPANY",
+          "LOC",
+          "O",
+          "ORG",
+          "PER",
+          "THING"
+        ],
+        "_type": "ClassLabel"
+      },
+      "_type": "Sequence"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 2904,
+      "num_examples": 23,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "data-00000-of-00001.arrow"
+    }
+  ],
+  "_fingerprint": "5f28155b25dfce47",
+  "_format_columns": [
+    "tags",
+    "tokens"
+  ],
+  "_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": {
+    "tokens": {
+      "feature": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "_type": "Sequence"
+    },
+    "tags": {
+      "feature": {
+        "names": [
+          "COMPANY",
+          "LOC",
+          "O",
+          "ORG",
+          "PER",
+          "THING"
+        ],
+        "_type": "ClassLabel"
+      },
+      "_type": "Sequence"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "valid": {
+      "name": "valid",
+      "num_bytes": 716,
+      "num_examples": 6,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "data-00000-of-00001.arrow"
+    }
+  ],
+  "_fingerprint": "72a47087be2f9285",
+  "_format_columns": [
+    "tags",
+    "tokens"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_output_all_columns": false,
+  "_split": null
+}