Processed data from AutoTrain data processor ([2023-06-26 17:20 ]

README.md

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+---
+task_categories:
+- token-classification
+
+---
+# AutoTrain Dataset for project: bert-political-statements-and-questions-swedish-ner
+
+## Dataset Description
+
+This dataset has been automatically processed by AutoTrain for project bert-political-statements-and-questions-swedish-ner.
+
+### 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
+[
+  {
+    "tokens": [
+      "KD",
+      "ska",
+      "f\u00f6rhandla",
+      "v\u00e5rbudget",
+      "med",
+      "Milj\u00f6partiet"
+    ],
+    "tags": [
+      1,
+      6,
+      6,
+      6,
+      6,
+      1
+    ]
+  },
+  {
+    "tokens": [
+      "V\u00e4nsterpartiet",
+      "ska",
+      "diskutera",
+      "h\u00f6stbudget",
+      "med",
+      "Sverigedemokraterna"
+    ],
+    "tags": [
+      1,
+      6,
+      6,
+      6,
+      6,
+      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=['B-LOC', 'B-ORG', 'B-PER', 'I-LOC', 'I-ORG', 'I-PER', 'UNK'], 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        | 3147 |
+| valid        | 821 |

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": {
+    "tokens": {
+      "feature": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "_type": "Sequence"
+    },
+    "tags": {
+      "feature": {
+        "names": [
+          "B-LOC",
+          "B-ORG",
+          "B-PER",
+          "I-LOC",
+          "I-ORG",
+          "I-PER",
+          "UNK"
+        ],
+        "_type": "ClassLabel"
+      },
+      "_type": "Sequence"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 568154,
+      "num_examples": 3147,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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+    }
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+  "_fingerprint": "c321008d65ca76ae",
+  "_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": [
+          "B-LOC",
+          "B-ORG",
+          "B-PER",
+          "I-LOC",
+          "I-ORG",
+          "I-PER",
+          "UNK"
+        ],
+        "_type": "ClassLabel"
+      },
+      "_type": "Sequence"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "valid": {
+      "name": "valid",
+      "num_bytes": 149472,
+      "num_examples": 821,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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+{
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+    }
+  ],
+  "_fingerprint": "73010bc1555acb68",
+  "_format_columns": [
+    "tags",
+    "tokens"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_output_all_columns": false,
+  "_split": null
+}