u/Jumixe2

Hi everyone,

I am looking for a dedicated study partner to collaborate on Transformer Architectures & Fine-Tuning. I’m currently working through an intensive program and need to complete the drills and labs for this week ASAP.

What we will be covering:

• Architectural Families: Understanding the differences between Encoder (BERT), Decoder (GPT), and Encoder-Decoder (T5) models.
• The Fine-Tuning Paradigm: Transitioning from pre-training to task-specific adaptation.
• Hands-on with Hugging Face: Preparing labeled datasets, tokenization (truncation & dynamic padding), and using the Trainer API.
• Evaluation: Implementing compute_metrics to calculate Accuracy and Macro-F1 scores.

My Technical Background:

• AI Engineer with a CS background from Yarmouk University.
• Experience with Python (NumPy, Pandas), SQL, and earlier NLP foundations.
• Comfortable with VS Code, Git, and pushing models to the Hugging Face Hub.

What I'm looking for: Someone who has a solid grasp of Python and basic ML, and is ready to jump into a DistilBERT fine-tuning lab immediately. We will be working on sentiment classification using app-review datasets.

If you're interested in a focused, high-intensity study session to master these concepts together, please DM me or comment below!