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Fine-tune your Classifier: Finding Correlations With Temperature
Temperature is a widely used hyperparameter in various tasks involving neural networks, such as classification or metric learning, whose choice can have a direct impact on the model performance.
What can we Learn by Predicting Accuracy?
The formula discovered on more than 260 datasets of embeddings has a Pearson's correlation of 0. 96 and a $r^2$ of 0. 93.
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