AI Glossary Term

What is Training Loss?

Definition

The model error value computed during training and optimized downward over time.

Related terms

Loss Function
A mathematical objective that quantifies prediction error during training.
Model Drift
Performance degradation over time as real-world conditions diverge from training assumptions.
Test-Time Compute
Additional inference computation used during response generation to improve quality or reasoning.
Data Drift
A shift in real-world input data over time that can degrade model performance.
Hyperparameter
A configuration value set before training, such as learning rate, batch size, or depth.
Knowledge Cutoff
The latest point in time reflected in a model's training data.

Learn more in our free guides

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