What is Fine -Tuning ? Explained in short
Fine-Tuning involves taking a pre-trained model, which has been trained on a large dataset for a general task such as image recognition or natural language understanding, and making minor adjustments to its internal parameters. The goal is to optimize the model’s performance on a new, related task without starting the training process from scratch.
Why Use Fine-Tuning?
1. IT saves time and resources by using what's already learned, skipping some training steps, and adapting well to specific jobs.
2.Pre-trained models come with learned features and patterns from vast data, which, when fine-tuned, boost performance for similar tasks by leveraging this knowledge.
3. Fine-tuning lets us train models even when we have limited labeled data. By tweaking pre-trained models for our task, we can get good results with less effort.
I am Fine-Tuning stable Stable Diffusion for Image Generation if you want to known more check my YT channel - / @exploration_ai
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