The dataset for the given notebook can be downloaded from Kaggle.
This dataset consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.
The data includes:
- Reviews from Oct 1999 - Oct 2012
- 568,454 reviews
- 256,059 users
- 74,258 products
- 260 users with > 50 reviews
Here, we perform sentiment analysis on a dataset of product reviews using the CLIP (Contrastive Language-Image Pre-Training) model. The code uses the pre-trained CLIP model provided by OpenAI and fine-tunes it on a dataset of product reviews. For more detailed explaination check out my article, Unleashing the Potential of Zero-Shot Classification with Contrastive Learning Using CLIP on Medium.