Best ChatGPT prompts for Models

Assume I am an expert prompt engineer and I need to evaluate a BERT model's performance on the task of predicting customer sentiment based on product reviews. Please provide a 10-page report comparing the baseline BERT model with the fine-tuned BERT model, highlighting the key differences in accuracy, F1 score, and precision, and suggesting areas for improvement.

I want to fine-tune a pre-trained RoBERTa model on a custom dataset of 10,000 product descriptions with corresponding sentiment labels. Please generate a list of optimal hyperparameters (learning rate, batch size, number of epochs, etc.) for this task, along with a recommended architecture and configuration for training and validation datasets.

Assume I need to deploy a BERT-based model as a RESTful API to classify customer feedback as positive, negative, or neutral. Please generate a Python code snippet to create the API, defining the model loading, input processing, inference, and output formatting, and provide documentation on how to use the API.