Initial commit of custom summarization dataset

README.md

@@ -1,10 +1,51 @@
----
-license: cc-by-4.0
-task_categories:
-- summarization
-language:
-- en
-pretty_name: Custom CNN/Daily Mail Summarization Dataset
-size_categories:
-- n<1K
----
+
+# Dataset Card for Custom Text Dataset
+
+## Dataset Name
+Custom CNN/Daily Mail Summarization Dataset
+
+## Overview
+This dataset is a custom version of the CNN/Daily Mail dataset, designed for text summarization tasks. It contains news articles and their corresponding summaries.
+
+## Composition
+The dataset consists of two splits:
+- Train: 1 custom example
+- Test: 100 examples from the original CNN/Daily Mail dataset
+
+Each example contains:
+- 'sentence': The full text of a news article
+- 'labels': The summary of the article
+
+## Collection Process
+The training data is a custom example created manually, while the test data is sampled from the CNN/Daily Mail dataset (version 3.0.0) available on Hugging Face.
+
+## Preprocessing
+No specific preprocessing was applied beyond the original CNN/Daily Mail dataset preprocessing.
+
+## How to Use
+```python
+from datasets import load_from_disk
+
+# Load the dataset
+dataset = load_from_disk("./results/custom_dataset/")
+
+# Access the data
+train_data = dataset['train']
+test_data = dataset['test']
+
+# Example usage
+print(train_data['sentence'])
+print(train_data['labels'])
+```
+
+## Evaluation
+This dataset is intended for text summarization tasks. Common evaluation metrics include ROUGE scores, which measure the overlap between generated summaries and reference summaries.
+
+## Limitations
+- The training set is extremely small (1 example), which may limit its usefulness for model training.
+- The test set is a subset of the original CNN/Daily Mail dataset, which may not represent the full diversity of news articles.
+
+## Ethical Considerations
+- The dataset contains news articles, which may include sensitive or biased content.
+- Users should be aware of potential copyright issues when using news content for model training or deployment.
+- Care should be taken to avoid generating or propagating misleading or false information when using models trained on this dataset.

test/dataset_dict.json

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+{"splits": ["test"]}

test/test/data-00000-of-00001.arrow

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test/test/dataset_info.json

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+{
+  "citation": "",
+  "description": "",
+  "features": {
+    "sentence": {
+      "feature": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "_type": "Sequence"
+    },
+    "labels": {
+      "feature": {
+        "dtype": "string",
+        "_type": "Value"
+      },
+      "_type": "Sequence"
+    }
+  },
+  "homepage": "",
+  "license": ""
+}

test/test/state.json

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+}

train/dataset_dict.json

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

train/train/data-00000-of-00001.arrow

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train/train/dataset_info.json

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+{
+  "citation": "",
+  "description": "",
+  "features": {
+    "sentence": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "labels": {
+      "dtype": "string",
+      "_type": "Value"
+    }
+  },
+  "homepage": "",
+  "license": ""
+}

train/train/state.json

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+      "filename": "data-00000-of-00001.arrow"
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+}