Processed data from AutoTrain data processor ([2023-08-01 21:46 ]

README.md

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+---
+language:
+- en
+task_categories:
+- text-classification
+
+---
+# AutoTrain Dataset for project: netflix-model
+
+## Dataset Description
+
+This dataset has been automatically processed by AutoTrain for project netflix-model.
+
+### 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
+[
+  {
+    "feat_show_id": "s7369",
+    "target": 1,
+    "text": "Mad Men",
+    "feat_director": null,
+    "feat_cast": "Jon Hamm, Elisabeth Moss, Vincent Kartheiser, January Jones, Christina Hendricks, Aaron Staton, Rich Sommer, John Slattery, Kiernan Shipka, Robert Morse, Michael Gladis, Christopher Stanley, Bryan Batt, Jared Harris, Jessica Par\u00e9, Alison Brie, Jay R. Ferguson, Ben Feldman, Mark Moses, Alexa Alemanni, Julie McNiven",
+    "feat_country": "United States",
+    "feat_date_added": " March 22, 2015",
+    "feat_release_year": 2014,
+    "feat_rating": "TV-14",
+    "feat_duration": "7 Seasons",
+    "feat_listed_in": "TV Dramas",
+    "feat_description": "Set in 1960s New York City, this award-winning series takes a peek inside an ad agency during an era when the cutthroat business had a glamorous lure."
+  },
+  {
+    "feat_show_id": "s8428",
+    "target": 0,
+    "text": "The Monster of Mangatiti",
+    "feat_director": "John Banas",
+    "feat_cast": "Greta Gregory, Mark Mitchinson, Bruce Hopkins, John Sumner, Flynn Allen, Harriet Beattie, Carolyn Dando, Laurie Dee, Ruth Dudding",
+    "feat_country": "New Zealand",
+    "feat_date_added": "December 15, 2015",
+    "feat_release_year": 2015,
+    "feat_rating": "TV-MA",
+    "feat_duration": "70 min",
+    "feat_listed_in": "Dramas",
+    "feat_description": "Real events are dramatized in the unthinkable story of a resilient teenager held prisoner by a seasoned predator on a remote farm in the 1980s."
+  }
+]
+```
+
+### Dataset Fields
+
+The dataset has the following fields (also called "features"):
+
+```json
+{
+  "feat_show_id": "Value(dtype='string', id=None)",
+  "target": "ClassLabel(names=['Movie', 'TV Show'], id=None)",
+  "text": "Value(dtype='string', id=None)",
+  "feat_director": "Value(dtype='string', id=None)",
+  "feat_cast": "Value(dtype='string', id=None)",
+  "feat_country": "Value(dtype='string', id=None)",
+  "feat_date_added": "Value(dtype='string', id=None)",
+  "feat_release_year": "Value(dtype='int64', id=None)",
+  "feat_rating": "Value(dtype='string', id=None)",
+  "feat_duration": "Value(dtype='string', id=None)",
+  "feat_listed_in": "Value(dtype='string', id=None)",
+  "feat_description": "Value(dtype='string', 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        | 7044 |
+| valid        | 1763 |

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": {
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+      "dtype": "string",
+      "_type": "Value"
+    },
+    "target": {
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+        "Movie",
+        "TV Show"
+      ],
+      "_type": "ClassLabel"
+    },
+    "text": {
+      "dtype": "string",
+      "_type": "Value"
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+  "license": "",
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+      "num_examples": 7044,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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

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processed/valid/dataset_info.json

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+  "description": "AutoTrain generated dataset",
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+      "_type": "ClassLabel"
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+  "license": "",
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+      "num_examples": 1763,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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