What are the challenges of explaining the predictions of very large fine-tuned models?

Mar 16, 2020 ... This paper presents segmentation of multiple organ regions from non-contrast CT volume based on deep learning. Also, we report usefulness of fine-tuning. Modifying the "initial_epoch" arg when doing fine tuning and transfer learning. ... mrdbourke / tensorflow-deep-learning Public. Notifications You must be signed ... Oct 15, 2024 ... ... Fine-tuning deep learning architectures for early detection of oral cancer. In: 2nd International Symposium on Mathematical and ... 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. Nov 7, 2023 ... When fine-tuning, it's common to adjust the deeper layers of the model while keeping the initial layers fixed. The rationale is that the initial ... Dec 4, 2024 ... Ahmet Sarigün: CompassDock: Comprehensive Accurate Assessment Approach for Deep Learning-Based Molecular Docking in Inference and Fine-Tuning. This paper examines how well deep networks can diagnose various cancers using histopathology image processing. What is fine-tuning in machine learning and AI? ... Fine-tuning is the process of taking a pretrained machine learning model and further training it on a smaller, ... Jul 2, 2024 ... This study aims to enhance precision of a popular commercial DLAS product in rectal cancer radiotherapy by localized fine-tuning. The p3 family is recommended as the fastest for deep learning training, and this is recommended for fine-tuning a model. The following chart shows the number of ...