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# Dataset Card for Custom Text Dataset

## Dataset Name
Custom CNN/Daily mail dataset

## Overview
Modified an English dataset containing over 300,000 unique news articles written by journalists from CNN and the Daily Mail.

## Composition
- **Train Data**: 
    - Articles: A manually provided article about the Palestinian Authority joining the International Criminal Court.
    - Labels: A manually written summary for the corresponding article.
    
- **Test Data**: 
    - Articles: 100 articles extracted from the original CNN/Daily Mail test set.
    - Labels: 100 corresponding summaries from the original dataset.

## Collection Process
The train data in this custom dataset was created manually by selecting a specific article and writing a corresponding summary. For the test data, 100 articles and their summaries were sampled from the CNN/Daily Mail dataset.

## Preprocessing
For the train set, no additional preprocessing was applied as the data was manually created. The test set was selected directly from the CNN/Daily Mail dataset without modification.


## How to Use
```python
from datasets import load_from_disk

# Load the custom train and test datasets
train_dataset = load_from_disk('./results/custom_dataset/train')
test_dataset = load_from_disk('./results/custom_dataset/test')

# Example of accessing the data
print(train_dataset['train'][0]['sentence'])
print(test_dataset['test'][0]['sentence'])
```

## Evaluation
Evaluation of this dataset could be done using text summarization models

## Limitations
The training dataset contains only one example, so it is not sufficient for training a model. 

## Ethical Considerations
- **Privacy**: Ensure that the data does not contain personal information.
- **Bias**: Be aware of potential biases in the data.

