What are the considerations when fine tuning models for fairness and preventing discriminatory outcomes?

This tutorial will walk through the process of transfer learning from a pre-trained network and a minimal approach to hyperparamater tuning. Jan 10, 2025 ... Specialization: Fine-tuning lets you customize a model to excel at a specific task. It's like tailoring a versatile suit to fit an individual. Dec 4, 2019 ... We then combine BERT with a one-dimensional convolutional neural network (1d-CNN) to fine-tune the pre-trained model for relation extraction. The comparative analysis attempts to find which approach is more efficient to be used for fine-tuning of pretrained BERT family transformer to deal with a ... Nov 21, 2017 ... Fine-tuning is a way of applying or utilizing transfer learning. Specifically, fine-tuning is a process that takes a model that has already been ... Jun 18, 2017 ... Can anyone share his code for using finetuning alexnet please? I am very new to all pytorch and deep learning and it would really help. Feb 13, 2025 ... Fine-tuning is a form of transfer learning where the pre-trained model is adjusted to better fit the new data. There are several steps involved ... Sep 11, 2023 ... Supervised fine-tuning (SFT) is the first training step within the alignment process for LLMs, and it is actually quite simple. First, we need ... This paper examines how well deep networks can diagnose various cancers using histopathology image processing. In this work, the focus was on fine-tuning and evaluation of state-of-the-art deep convolutional neural network for image-based plant disease classification.