abhuse/polyloss-pytorch
Polyloss Pytorch Implementation
This project offers an implementation of PolyLoss within the PyTorch framework, specifically designed to enhance classification tasks in machine learning. It takes raw prediction scores (logits) and corresponding true labels as input, and outputs a refined loss value used to train more accurate classification models. This is for machine learning engineers and researchers who are building and training deep learning models for categorization problems.
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Use this if you are training deep learning classification models in PyTorch and want to experiment with advanced loss functions (Poly-Cross-Entropy or Poly-Focal Loss) to improve model performance, especially in scenarios with imbalanced classes or challenging samples.
Not ideal if you are working with non-PyTorch frameworks, regression problems, or if you prefer a simpler, out-of-the-box loss function without fine-tuning parameters like epsilon, alpha, or gamma.
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45
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7
Language
Python
License
MIT
Category
Last pushed
May 09, 2022
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