autotrain Adult 934630783

Introduction

This project involves a binary classification model trained using Hugging Face's AutoTrain. It utilizes tabular data to make predictions and has been optimized for accuracy and efficiency.

Architecture

The model is designed for tabular classification tasks and employs the joblib library for model storage and retrieval. It is a part of the Hugging Face model repository under the identifier AUTOTRAIN-ADULT-934630783.

Training

The model was trained with the dataset rajistics/autotrain-data-Adult. It achieved the following validation metrics:

• Loss: 0.298
• Accuracy: 86.28%
• Precision: 78.73%
• Recall: 59.09%
• AUC: 91.82%
• F1 Score: 67.51%

CO2 emissions during training were estimated at 38.42 grams.

Guide: Running Locally

To run this model locally, follow these steps:

1. Install Dependencies: Ensure you have joblib and pandas installed. You can install them using pip:

   pip install joblib pandas
   

2. Load the Model: Use the following code snippet to load and utilize the model:

   import json
   import joblib
   import pandas as pd
   
   model = joblib.load('model.joblib')
   config = json.load(open('config.json'))
   
   features = config['features']
   
   # Load your dataset
   # data = pd.read_csv("data.csv")
   data = data[features]
   data.columns = ["feat_" + str(col) for col in data.columns]
   
   predictions = model.predict(data)  # or model.predict_proba(data)
   

3. Consider Cloud GPUs: For enhanced performance, especially with larger datasets, consider using cloud GPU services such as AWS, Google Cloud, or Azure.

License

This project and its contents are subject to the licensing terms outlined by Hugging Face's platform. Ensure you review these terms before using the model.