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Hi Ashok! Me and some classmates are planning to use this model for a project in uni. The project is about MLOps and the whole process of deploying a model, so we would like to know more details about the model and how it works. Of course we will check the code, but it's always good to have some insight from the person who made the thing :). If you need it, you can contact me at [email protected] .
Hi! I'd be happy to share some insights about the Amazon Sentiment Analysis model I developed. The model is based on GPT-2, a transformer-based language model, which I fine-tuned using Amazon user reviews from 2023. The purpose of fine-tuning GPT-2 was to adapt it specifically for understanding and generating text related to sentiment analysis in Amazon reviews.
During the fine-tuning process, I trained the model to recognize different sentiments (positive, negative, neutral) by leveraging real user feedback. The fine-tuned GPT-2 model can now predict the sentiment of new reviews by generating relevant responses or categorizing them based on the emotions conveyed in the text.
Thank you and your team!!!!
You can use my model by using API
import transformers
from transformers import pipeline
sentiment_model = pipeline(model="ashok2216/gpt2-amazon-sentiment-classifier")
Cool! Thank you Ashok. First of all we would like to know what data you used to train the model (and also for test) to replicate the results. We are assuming you did not use all the dataset.
I used this dataset for Fine-tuning
McAuley-Lab/Amazon-Reviews-2023