Finetuned Neural Network Model: Difference between revisions

From GM-RKB
Jump to navigation Jump to search
(Created page with "A Finetuned NNet Model is a Neural Network Model that has undergone a process known as Fine-Tuning. * <B>Context:</B> ** It can enhance the model's performance on specific tasks by continuing the training process on a task-specific dataset after the initial pretraining. ** It can leverage a large, generalized pre-trained model as a starting point, reducing the need for extensive data and computational resources typically required for training from scratch. **...")
 
(Redirected page to Finetuned NNet Model)
Tag: New redirect
 
Line 1: Line 1:
A [[Finetuned NNet Model]] is a [[Neural Network Model]] that has undergone a process known as [[Fine-Tuning]].
#REDIRECT [[Finetuned NNet Model]]
* <B>Context:</B>
** It can enhance the model's performance on specific tasks by continuing the training process on a task-specific dataset after the initial pretraining.
** It can leverage a large, generalized pre-trained model as a starting point, reducing the need for extensive data and computational resources typically required for training from scratch.
** It can range from simple architectures like [[Feedforward Neural Networks]] to complex ones like [[Transformers]] depending on the task and data.
** It can often result in significant improvements in accuracy and efficiency, particularly in domains like [[Image Recognition]], [[Natural Language Processing]], and [[Speech Recognition]].
** It can exhibit variation in performance depending on factors such as the size and quality of the finetuning dataset, initial model architecture, and the specificities of the task.
** ...
* <B>Example(s):</B>
** a [[Finetuned BERT Model]] ([[BERT model]]) finetuned for [[Question Answering]] that can accurately respond to queries based on context provided in a passage.
** a [[Finetuned ResNet Model]] ([[ResNet model]) finetuned for [[Skin Cancer Detection]] capable of identifying malignancies in dermatological images with high precision.
** ...
* <B>Counter-Example(s):</B>
** [[Generic Neural Network Model]]s that are only pretrained and not finetuned on specific task data.
** [[Untrained Neural Network Model]]s that have not undergone any form of training.
** ...
* <B>See:</B> [[Transfer Learning]], [[Domain-Specific Models]], [[Adaptive Learning]], [[Neural Network Architecture]]
 
----
----
 
== References ==
 
----
__NOTOC__

Latest revision as of 17:08, 25 April 2024

Redirect to:

Retrieved from "http://www.gabormelli.com/RKB/index.php?title=Finetuned_Neural_Network_Model&oldid=874223"