YoVDO

Evaluate LayoutLMv3 for Document Classification - Save & Load Model to HuggingFace Hub

Offered By: Venelin Valkov via YouTube

Tags

Natural Language Processing (NLP) Courses Machine Learning Courses Document Classification Courses Model Training Courses Confusion Matrix Courses

Course Description

Overview

Explore the performance of a pre-trained LayoutLMv3 model on unseen document image data in this comprehensive tutorial video. Learn how to upgrade libraries, save the best model, upload and load models from HuggingFace Hub, predict document image classes, and analyze predictions using a confusion matrix. Gain practical insights into document classification using deep learning techniques, with a focus on PyTorch and HuggingFace Transformers libraries.

Syllabus

- Intro
- Upgrade libraries
- Save the best model
- Upload your model to HuggingFace Hub
- Training metrics
- Load your model from HuggingFace Hub
- Predict the class of a document image
- Explore predictions using a confusion matrix
- Conclusion


Taught by

Venelin Valkov

Related Courses

Predict Housing Prices in R on Boston Housing Data
Coursera Project Network via Coursera Predict Gas Guzzlers using MPG Data Set and a Random Forest
Coursera Project Network via Coursera Predict Ideal Diamonds over Good Diamonds using a Random Forest using R
Coursera Project Network via Coursera Predict Gas Guzzlers using a Neural Net Model on the MPG Data Set
Coursera Project Network via Coursera Machine Learning: Predict Poisonous Mushrooms using a Random Forest Model and the FFTrees Package in R
Coursera Project Network via Coursera