Gradient Descent Calculator
Calculate gradient descent parameters, convergence rate, effective learning rate, and training time estimates.
Inputs
Results
Steps per Epoch
313
Total Steps
313,000
Effective Learning Rate
0.1
Convergence Rate0
Training Time1.67 minutes
Final Learning Rate0
Steps per Epoch
313
Total Steps
313,000
Effective Learning Rate
0.1
How to Use This Calculator
- Start by filling in the input fields below. Results update instantly as you type, so you can experiment with different values to see how they affect the outcome.
- Learning Rate — Learning rate (step size) Accepts values from 0.0001 to 1 (default: 0.01).
- Number of Iterations — Total training iterations Accepts values from 1 to 100,000 (default: 1,000).
- Momentum — Momentum coefficient Accepts values from 0 to 0.99 (default: 0.9).
- Batch Size — Samples per batch Accepts values from 1 to 10,000 (default: 32).
- Dataset Size — Total training samples Accepts values from 1 to 10,000,000 (default: 10,000).
- Once all inputs are set, review your results in the Results panel. Here's what each output means:
- Steps per Epoch — shown as a numeric value. This is the primary result of this calculator.
- Total Steps — shown as a numeric value. This is the primary result of this calculator.
- Effective Learning Rate — shown as a numeric value. This is the primary result of this calculator.
- Convergence Rate — shown as a numeric value.
- Training Time — shown as a numeric value.
- Final Learning Rate — shown as a numeric value.
- Explore the related calculators below if you need deeper analysis or want to approach this topic from a different angle.
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Formula
θ_new = θ_old - α × ∇J(θ)Related Calculators
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