> For the complete documentation index, see [llms.txt](https://opencampus.gitbook.io/opencampus-machine-learning-program/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/machine-learning-with-tensorflow/week-4-convolutional-neural-networks-part-i.md).

# Week 4 - Working with Text Using Hugging Face

### This week you will...

* Build an end-to-end NLP pipeline that classifies AG News articles into World, Sports, Business, or Sci/Tech.
* Use a pretrained DistilBERT tokenizer to convert raw text into model-ready inputs such as token IDs, attention masks, and labels.
* Implement a custom PyTorch `Dataset`, dynamic padding with a data collator, and `DataLoader`s for efficient training and validation.
* Fine-tune DistilBERT using partial layer freezing, tune key hyperparameters, evaluate performance, and save the trained model safely.

### Slides

{% file src="/files/cwHzOrjd9jBhAuHHlxE3" %}

### Additional Learning Resources

* [What is NLP](https://www.youtube.com/watch?v=fLvJ8VdHLA0) (9 min)
* [Embeddings explained](https://www.youtube.com/watch?v=wgfSDrqYMJ4\&t) (8 min)
* Awesome LLM [resource collection](https://github.com/hannibal046/awesome-llm)
* Hugging Face [Transformers Course](https://huggingface.co/learn/llm-course/chapter1/1)

### Until next week you should...

* Prepare questions for your projects for the feedback sessions
* Start on [Module 1: Hyperparameter Optimization](https://learn.deeplearning.ai/specializations/pytorch-for-deep-learning-professional-certificate/lesson/oppq8g/a-conversation-between-laurence-moroney-and-andrew-ng) of Course 2 (PyTorch: Techniques and Ecosystem Tools)
* Start on this [assignment notebook](https://colab.research.google.com/github/opencampus-sh/course-material/blob/main/applied-machine-learning/week-04/Week4_Notebook1_CIFAR-10.ipynb)


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