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README.md

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-This classifier is specifically used to identify sports text.
+# Sports Text Classifier
+
+## Overview
+
+This Sports Text Classifier is a crucial component of the OnlySports Dataset creation pipeline. It's designed to accurately identify and extract sports-related documents from a large corpus of web content.
+
+## Model Architecture
+
+- Base model: [Snowflake-arctic-embed-xs](https://huggingface.co/Snowflake/snowflake-arctic-embed-xs)
+- Additional layer: Binary classification layer
+- Training: 10 epochs with a learning rate of 3e-4
+
+## Performance
+
+The classifier achieves exceptional accuracy in distinguishing between sports and non-sports documents:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/656590bd40440ddcc051ade7/hK_a183i2_H5AfUF6ZXd6.png)
+
+## Training Data
+
+The classifier was trained on a balanced dataset of sports and non-sports content:
+
+- 64k samples from seven prestigious sports websites
+- 36k non-sports text documents classified using GPT-3.5
+
+## Usage
+
+This classifier is primarily used in the creation of the OnlySports Dataset. It can be applied to filter large text corpora for sports-related content with high accuracy.
+
+## Integration
+
+The classifier is integrated into a MapReduce architecture for efficient processing of large-scale datasets. It's used in conjunction with URL keyword filtering to create a comprehensive sports text dataset.
+
+## Related Projects
+
+This classifier is part of the larger OnlySports collection, which includes:
+
+- [OnlySports Dataset](https://huggingface.co/collections/Chrisneverdie/onlysports-66b3e5cf595eb81220cc27a6)
+- [OnlySportsLM](https://huggingface.co/Chrisneverdie/OnlySportsLM_196M)
+
+For more information, visit our [GitHub repository](https://github.com/chrischenhub/OnlySportsLM).