Text-Classification-project-with-fast.ai

It was done while learning NLP from Practical Deep Learning For Coders by Jeremy Howard. This project involves the implementation of a text classification model using PyTorch. The model is trained on the AG News dataset using a neural network architecture consisting of an embedding layer, a linear layer, and a cross-entropy loss function. The training and validation data are loaded using PyTorch's DataLoader and are preprocessed using a tokenizer and a vocabulary. The project also uses TensorBoard to visualize the training and validation loss and accuracy metrics. The final model achieves an accuracy of over 90% on the test dataset. It is one of the basic project used for learning demonstrationn but in future I would like to implement more advanced model to acheive higher accuracy.