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Interactive Tool

Training Loss Visualizer

See what a realistic training curve looks like. Identify convergence, diminishing returns, and the point where overfitting begins.

This chart shows two curves from a model training for 30 epochs. The training loss (dark line) keeps decreasing. The validation loss (gray line) decreases at first, then starts increasing — that is where overfitting begins. Learn more in Session 9.

0.0 0.5 1.0 1.5 2.0 0 5 10 15 20 25 30 EPOCH OVERFITTING BEGINS Validation loss starts rising CONVERGENCE Loss flattens, gains are tiny Training Loss Validation Loss

What to Look For

Epochs 0-10 (Rapid Learning): Both curves drop steeply. The model is learning the big, obvious patterns in the data. Each epoch produces large improvements.

Epochs 10-15 (Convergence): The curves flatten. Improvement slows dramatically. The model has learned most of what it can from the training data. This is where you want to stop.

Epochs 15-30 (Overfitting): Training loss keeps dropping (the model memorizes the data). But validation loss rises (the model fails on new data). The gap between the two curves is the overfitting signal. Stop training when validation loss starts climbing.