Processed data from AutoTrain data processor ([2023-01-23 15:00 ]

README.md

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+---
+task_categories:
+- text-classification
+
+---
+# AutoTrain Dataset for project: tktktk
+
+## Dataset Description
+
+This dataset has been automatically processed by AutoTrain for project tktktk.
+
+### 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
+[
+  {
+    "text": "@TK_TR 21 dk beklemem gerekti\u011fi s\u00f6yleniyor, m\u00fc\u015fteri temsilcisi ba\u011flanm\u0131yorum . \u0130nternet sitesinden de i\u015flem yap\u0131lam\u0131yor nas\u0131l \u00e7\u00f6z\u00fcm bulaca\u011f\u0131m ?",
+    "target": 0
+  },
+  {
+    "text": "@yhyustun Sevgili Yahya Bey Allah Rizasi icin bari sen bir aciklama yaparsan sevinirim.Konu su:Danimarkadan Turkiyeye ucuslar sistemde yok gorunuyor tum Mart ayi icin.1 Mart icin ucusum vardi fakat birkac gun once cagri merkeziyle gorustum ucuslar satisa kapanmis ancak bizim bir haberimiz",
+    "target": 0
+  }
+]
+```
+
+### Dataset Fields
+
+The dataset has the following fields (also called "features"):
+
+```json
+{
+  "text": "Value(dtype='string', id=None)",
+  "target": "ClassLabel(names=['negative', 'neutral', 'positive'], 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        | 2398 |
+| valid        | 601 |

processed/dataset_dict.json

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

processed/train/dataset.arrow

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processed/train/dataset_info.json

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+{
+  "citation": "",
+  "description": "AutoTrain generated dataset",
+  "features": {
+    "text": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "target": {
+      "names": [
+        "negative",
+        "neutral",
+        "positive"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 530577,
+      "num_examples": 2398,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "dataset.arrow"
+    }
+  ],
+  "_fingerprint": "47524bd15d611e0d",
+  "_format_columns": [
+    "target",
+    "text"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_indexes": {},
+  "_output_all_columns": false,
+  "_split": null
+}

processed/valid/dataset.arrow

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+size 128136

processed/valid/dataset_info.json

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+{
+  "citation": "",
+  "description": "AutoTrain generated dataset",
+  "features": {
+    "text": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "target": {
+      "names": [
+        "negative",
+        "neutral",
+        "positive"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "valid": {
+      "name": "valid",
+      "num_bytes": 127518,
+      "num_examples": 601,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "dataset.arrow"
+    }
+  ],
+  "_fingerprint": "90cbd168f4987ef1",
+  "_format_columns": [
+    "target",
+    "text"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_indexes": {},
+  "_output_all_columns": false,
+  "_split": null
+}