transformers safetensors deberta-v2 text-classification autotrain en dataset:autotrain-nndq9-1xgjv/autotrain-data license:mit autotrain_compatible endpoints_compatible region:us
---
datasets:
- autotrain-nndq9-1xgjv/autotrain-data
language:
- en
license: mit
pipeline_tag: text-classification
tags:
- autotrain
- text-classification
widget:
- text: What are the latest updates on the NBA trade deadline?
---
# Sports Stats Questions Classifier

description: 
  Welcome to the Sports Stats Questions Classifier! This NLP-based text classification tool is designed to classify sports-related questions into different categories based on their content. Whether you're a sports enthusiast, journalist, or data analyst, this tool can help you quickly categorize and organize sports-related queries with ease.

overview:
    This project utilizes natural language processing (NLP) techniques to understand and classify questions related to sports statistics. By analyzing the text of the questions, the classifier assigns them to predefined categories, such as "scores," "players," "stats," "teams," "games," "standings," "schedules," "rosters," or "news."

features:
  - Text Classification: Classify sports stats questions into predefined categories.
  - Fast and Efficient: Utilizes state-of-the-art NLP models for quick and accurate classification.
  - Easy Integration: Can be integrated into various applications, websites, or chatbots for seamless user interaction.
  - Customizable: Easily extend or modify the categories and training data to suit your specific needs.
  - User-Friendly: Simple and intuitive interface for easy usage by both developers and end-users.

ontributing: |
  Contributions are welcome! If you have any suggestions, feature requests, or bug reports, please open an issue or submit a pull request on GitHub.

license: MIT

contact: |
  Feel free to reach out to us with any questions, feedback, or collaboration opportunities. Happy classifying! 🏀🏈⚽️
---
tags:
- autotrain
- text-classification
widget:
- text: "What are the latest updates on the NBA trade deadline?"
datasets:
- autotrain-nndq9-1xgjv/autotrain-data
---

# Model Trained Using AutoTrain

- Problem type: Text Classification

## Validation Metrics
loss: 1.0594602823257446

f1_macro: 0.703125

f1_micro: 0.8518518518518519

f1_weighted: 0.7916666666666666

precision_macro: 0.6722222222222223

precision_micro: 0.8518518518518519

precision_weighted: 0.7497942386831277

recall_macro: 0.75

recall_micro: 0.8518518518518519

recall_weighted: 0.8518518518518519

accuracy: 0.8518518518518519