voxmenthe/modernbert-imdb-sentiment

ModernBERT IMDb Sentiment Analysis Model

Model Description

Fine-tuned ModernBERT model for sentiment analysis on IMDb movie reviews. Achieves 95.75% accuracy on the test set.

Usage

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("voxmenthe/modernbert-imdb-sentiment")
tokenizer = AutoTokenizer.from_pretrained("answerdotai/ModernBERT-base")

# Input processing
inputs = tokenizer("This movie was fantastic!", return_tensors="pt")
outputs = model(**inputs)

# Get the predicted class
predicted_class_id = outputs.logits.argmax().item()

# Convert class ID to label
predicted_label = model.config.id2label[predicted_class_id]
print(f"Predicted label: {predicted_label}")

Model Card

Model Details

• Model Name: ModernBERT IMDb Sentiment Analysis
• Base Model: answerdotai/ModernBERT-base
• Task: Sentiment Analysis
• Dataset: IMDb Movie Reviews
• Training Epochs: 5

Model Performance

• Test Accuracy: 95.75%
• Test F1 Score: 95.75%

Model Architecture

• Base Model: answerdotai/ModernBERT-base
• Task-Specific Head: ClassifierHead (from classifiers.py)
• Number of Labels: 2 (Positive, Negative)

Model Inference

• Input Format: Text (single review)
• Output Format: Predicted sentiment label (Positive or Negative)

Model Version

• Version: 1.0
• Date: 2025-05-07

Model License

• License: MIT License

Model Contact

• Contact: alocalminima@gmail.com

Model Citation

• Citation: voxmenthe/modernbert-imdb-sentiment

IMDb Sentiment Analyzer - Gradio App

This repository contains a Gradio application for sentiment analysis of IMDb movie reviews. It uses a fine-tuned ModernBERT model hosted on Hugging Face.

Space Link: voxmenthe/imdb-sentiment-demo Model Link: voxmenthe/modernbert-imdb-sentiment

Features

• Text Input: Analyze custom movie review text.
• Random IMDb Sample: Load a random review from the IMDb test dataset.
• Sentiment Prediction: Classifies sentiment as Positive or Negative.
• True Label Display: Shows the actual IMDb label for loaded samples.

Setup & Running Locally

1. Clone the repository (or your Space repository):

   git clone https://huggingface.co/spaces/voxmenthe/imdb-sentiment-demo
   cd imdb-sentiment-demo
   

2. Install dependencies: Ensure you have Python 3.11+ installed.

   pip install -r requirements.txt
   

3. Run the application:

   python app.py
   

   The application will be available at http://127.0.0.1:7860.

Model Information

The sentiment analysis model is a ModernBERT architecture fine-tuned on the IMDb dataset. The specific checkpoint used is mean_epoch5_0.9575acc_0.9575f1.pt before being uploaded to voxmenthe/modernbert-imdb-sentiment.