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| # Dataset Card for Custom Text Dataset |
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|
| ## Dataset Name |
| Custom Text Dataset |
|
|
| ## Overview |
| This dataset contains text data for training language models. |
| The data is collected from various sources, including books, articles, |
| and web pages. |
|
|
| ## Composition |
| - **Number of records**: 101 |
| - **Fields**: `sentence`, `labels` |
| - **Size**: 510 KB |
|
|
| ## Collection Process |
| The data was collected using web scraping and manual extraction |
| from public domain sources. |
|
|
| ## Preprocessing |
| - Removed HTML tags and special characters |
| - Tokenized text into sentences |
|
|
| ## How to Use |
| ```python |
| from datasets import load_dataset |
| dataset = load_dataset("path_to_dataset") |
| |
| for example in dataset["train"]: |
| print(example["sentence"]) |
| ``` |
|
|
| ## Evaluation |
| This dataset is designed for evaluating text generation models. |
| Common evaluation metrics include ROUGE and BLEU. |
|
|
| ## Limitations |
| The dataset may contain outdated or biased information. |
| Users should be aware of these limitations when using the data. |
|
|
| ## Ethical Considerations |
| Privacy: Ensure that the data does not contain personal information. |
| Bias: Be aware of potential biases in the data. |
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