What are the benefits and challenges of fine-tuning a pre-trained model?
Answer / Nishtnt Kumar Ramteke
Benefits of fine-tuning a pre-trained model include: 1. Lower training time compared to starting from scratch; 2. Reduced risk of overfitting due to the pre-trained model's generalization ability; 3. Improved performance on specific tasks through targeted adaptation. However, challenges include: 1. Limited control over the pre-trained model's learning process; 2. Potential mismatch between the pre-trained and fine-tuning datasets; 3. Requiring access to high-quality pre-trained models.
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