Learning how to finetune a BERT model using PyTorch/TensorFlow from HuggingFace for your usecase is a art in itself
because there are so many ways and methods to do it that you will not able to figure out which is the best for my
usecase. BTW, you can always refer to HuggingFace documentation.
For example!
Choose between PyTorch and TensorFlow. (let choose )
If you are importing your dataset with pandas or polars then need to create a custom class by inheriting
torch.utils.data.Dataset class.
Then need to tokenize the data and need to use DataLoader and Data Collator.
Then use a for-loop to train and validate the model.
As the shape of data increases the ML models cannot able to capture its underlying patterns but deep learning
algorithms capture the complex relationship very well.
ML algorithms uses different techniques to learn patterns from data like linear line, spliting criteria, etc. but
Perceptron is the building block of DL algorithms which helps to capture almost every patterns of the data.
By implementing these strategies, you can elevate your Resume/CV to effectively communicate your qualifications and stand out among the competition in today's job market.