BERT Fine-tuning Cost & Time Estimator
Calculate GPU hours, training time, and cloud costs for fine-tuning BERT, RoBERTa, and other transformer models. Supports AWS SageMaker, GCP Vertex AI, Azure ML, and self-hosted options.
Model Selection
Dataset
Training Config
Hardware
Cloud Provider
How This Calculator Works
Training Steps: (Training Examples ÷ Batch Size) × Epochs
GPU Hours: Training Time (hours) × Number of GPUs
Memory: Estimated based on model size, batch size, and sequence length
Cost: GPU Hours × Hourly Rate (varies by provider and GPU type)
Speed: FP16 mixed precision is ~2x faster but uses less memory. Multi-GPU training reduces per-GPU training time but doesn't reduce total compute cost.
Pricing Notes
- AWS SageMaker: On-demand pricing. Spot instances available at 70% discount.
- GCP Vertex AI: Per-GPU pricing. May require minimum commitment.
- Azure ML: Compute instances billed hourly. Requires storage for checkpoints.
- EC2 Spot: 80-90% cheaper than on-demand, but can be interrupted.
- Self-hosted: Only shows electricity cost (assumes ~$0.10/kWh). Add hardware amortization.
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