Transfer Learning for NLP with TensorFlow Hub

This project demonstrates the use of various pre-trained models for transfer learning in NLP using TensorFlow Hub.

Training Results

Model	Epoch	Accuracy	Loss	Val Accuracy	Val Loss
gnews-swivel-20dim	0	0.9331	0.2729	0.9381	0.1989
nnlm-en-dim50	0	0.9339	0.3251	0.9381	0.2252
gnews-swivel-20dim-finetuned	0	0.9337	0.3145	0.9381	0.2124
nnlm-en-dim128	0	0.9213	0.3408	0.9381	0.2256
universal-sentence-encoder	0	0.9344	0.3153	0.9381	0.1770
universal-sentence-encoder-large	0	0.9365	0.2923	0.9381	0.1682

This table provides a quick overview of the training results for each model, including accuracy, loss, and validation metrics.

Summary of Training Results

• The models were trained for one epoch each.
• The accuracy of the models ranged from 92.13% to 93.65%.
• The loss values varied between 0.2729 and 0.3408.
• All models achieved a validation accuracy of 93.81%.
• The validation loss ranged from 0.1682 to 0.2256.

This summary provides a concise overview of the training performance across different models.