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<!-- Provide a quick summary of the dataset. -->
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This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
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## Dataset Details
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### Dataset Description
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<!-- Provide a longer summary of what this dataset is. -->
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- **Curated by:** [
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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### Dataset Sources [optional]
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- **Repository:** [
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the dataset is intended to be used. -->
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### Direct Use
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<!-- This section describes suitable use cases for the dataset. -->
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[More Information Needed]
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## Dataset Structure
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## Dataset Creation
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### Curation Rationale
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<!-- Motivation for the creation of this dataset. -->
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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#### Data Collection and Processing
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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#### Who are the source data producers?
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<!-- Provide a quick summary of the dataset. -->
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## Dataset Details
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### Dataset Description
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- **Curated by:** [Amit Kedia](https://www.linkedin.com/in/theamitkedia/)
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- **Language(s) (NLP):** English
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- **License:** Apache 2.0
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### Dataset Sources [optional]
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<!-- Provide the basic links for the dataset. -->
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- **Repository:** [GitHub](https://github.com/amitkedia007/Financial-Fraud-Detection-Using-LLMs)
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- **Thesis:** [Financial Fraud Detection using LLMs](https://github.com/amitkedia007/Financial-Fraud-Detection-Using-LLMs/blob/main/Detailed_Report_on_financial_fraud_detection.pdf)
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## Uses
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### Direct Use
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<!-- This section describes suitable use cases for the dataset. -->
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#### Code to Directly use the dataset:
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from datasets import load_dataset
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dataset = load_dataset("amitkedia/Financial-Fraud-Dataset")
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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There are some limitations of the dataset:
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1. This dataset is designed for acedemic research
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2. The text needs to be cleaned for further process
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3. The dataset does not cover all the fradulent cases and are limited to Securities and Exchange Commision of USA (SEC) that means the fradulent and non fradulent cases are the companies of USA
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## Dataset Structure
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For the structure of the dataset look into the dataset viewer.
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## Dataset Creation
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Check out the Thesis
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### Curation Rationale
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<!-- Motivation for the creation of this dataset. -->
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To help the financial industry to develop best model to detect the fraudulent activities which can save billions of dollars of government and banks
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#### Data Collection and Processing
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#### Who are the source data producers?
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