Processed data from AutoTrain data processor ([2023-05-03 12:43 ]

README.md

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+---
+task_categories:
+- text-classification
+
+---
+# AutoTrain Dataset for project: sachin-test-summarizer
+
+## Dataset Description
+
+This dataset has been automatically processed by AutoTrain for project sachin-test-summarizer.
+
+### 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": "\u2212 Scope 3: Optional scope that includes indirect emissions associated with the goods and services supply chain produced outside the organization. Included are emissions from the transport of products from our logistics centres to stores (downstream) performed by external logistics operators (air, land and sea transport) as well as the emissions associated with electricity consumption in franchise stores.",
+    "target": 1
+  },
+  {
+    "text": "The Group is not aware of any noise pollution that could negatively impact the environment, nor is it aware of any impact on biodiversity. With regards to land use, the Group is only a commercial user, and the Group is not aware of any local constraints with regards to water supply. The Group does not believe that it is at risk with regards to climate change in the near-or mid-term.",
+    "target": 0
+  }
+]
+```
+
+### Dataset Fields
+
+The dataset has the following fields (also called "features"):
+
+```json
+{
+  "text": "Value(dtype='string', id=None)",
+  "target": "ClassLabel(names=['0', '1', '2'], 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        | 1000 |
+| valid        | 320 |

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": {
+    "text": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "target": {
+      "names": [
+        "0",
+        "1",
+        "2"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 491359,
+      "num_examples": 1000,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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+    {
+      "filename": "data-00000-of-00001.arrow"
+    }
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+  "_fingerprint": "8ae14147116ebc3e",
+  "_format_columns": [
+    "target",
+    "text"
+  ],
+  "_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": {
+    "text": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "target": {
+      "names": [
+        "0",
+        "1",
+        "2"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "valid": {
+      "name": "valid",
+      "num_bytes": 174265,
+      "num_examples": 320,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "data-00000-of-00001.arrow"
+    }
+  ],
+  "_fingerprint": "980c493c3e60fa87",
+  "_format_columns": [
+    "target",
+    "text"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_output_all_columns": false,
+  "_split": null
+}