A step-to-step guide to navigate you through training your own transformer-based language model.

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A step-by-step guide for building and training a transformer-based language model using Hugging Face Transformers. The process covers installing necessary libraries, loading and tokenizing the dataset, initializing and configuring the model (BERT for sequence classification), setting up the training loop with TrainingArguments and Trainer, and finally training the model. Emphasis is given on the computational resources required for training and troubleshooting common issues.

How to Build and Train a Transformer Model from Scratch with Hugging Face Transformers