Processed data from AutoTrain data processor ([2023-01-03 12:42 ]

README.md

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+---
+task_categories:
+- summarization
+
+---
+# AutoTrain Dataset for project: exact_data
+
+## Dataset Description
+
+This dataset has been automatically processed by AutoTrain for project exact_data.
+
+### 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": "What is the maximum vendor id of vendor present in vendor table who has been issued a PO in 2021",
+    "target": "select max(t1.vendor_id) from RETAILBUYER_POHEADER as t2 inner join RETAILBUYER_VENDOR as t1 on t2.vendor_id = t1.vendor_id where YEAR(t2.po_issuedt) = 2021"
+  },
+  {
+    "text": "What are the product ids, descriptions and sum of quantities ordered for the products in purchase order line items",
+    "target": "select L.product_id, t2.product_desc, sum(t1.quantity) from RETAILBUYER_PRODUCT_SOURCE as t2 INNER JOIN RETAILBUYER_POLINEITEM as t1 ON t2.PRODUCT_ID = t1.PRODUCT_ID GROUP BY t1.PRODUCT_ID, t2.product_desc"
+  }
+]
+```
+
+### Dataset Fields
+
+The dataset has the following fields (also called "features"):
+
+```json
+{
+  "text": "Value(dtype='string', id=None)",
+  "target": "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        | 25 |
+| valid        | 7 |

processed/dataset_dict.json

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

processed/train/dataset.arrow

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+size 7000

processed/train/dataset_info.json

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+{
+  "citation": "",
+  "description": "AutoTrain generated dataset",
+  "features": {
+    "text": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "target": {
+      "dtype": "string",
+      "_type": "Value"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 6405,
+      "num_examples": 25,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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+      "filename": "dataset.arrow"
+    }
+  ],
+  "_fingerprint": "6da3a8f9defc9dd5",
+  "_format_columns": [
+    "target",
+    "text"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_indexes": {},
+  "_output_all_columns": false,
+  "_split": null
+}

processed/valid/dataset.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": {
+      "dtype": "string",
+      "_type": "Value"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "valid": {
+      "name": "valid",
+      "num_bytes": 1890,
+      "num_examples": 7,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "dataset.arrow"
+    }
+  ],
+  "_fingerprint": "53bcce698b7ff08e",
+  "_format_columns": [
+    "target",
+    "text"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_indexes": {},
+  "_output_all_columns": false,
+  "_split": null
+}