Steps in Fine-Tuning #621

CipherScr1be · 2025-02-23T00:27:43Z

CipherScr1be
Feb 23, 2025

describe brifely steps in fine-tuning

Answered by Sachin-NK

Select a Pre-trained Model – Use models like GPT, BERT, ResNet, etc.
Freeze Initial Layers – Preserve general features while training only later layers.
Train on New Data – Use domain-specific data with a lower learning rate.
Regularization – Prevent overfitting with dropout, early stopping, or data augmentation.
Evaluate & Optimize – Fine-tune hyperparameters for better results.

Sachin-NK · 2025-02-23T00:28:46Z

Select a Pre-trained Model – Use models like GPT, BERT, ResNet, etc.
Freeze Initial Layers – Preserve general features while training only later layers.
Train on New Data – Use domain-specific data with a lower learning rate.
Regularization – Prevent overfitting with dropout, early stopping, or data augmentation.
Evaluate & Optimize – Fine-tune hyperparameters for better results.

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