metadata

language: en
tags:
  - sentiment-analysis
  - modernbert
  - imdb
datasets:
  - imdb
metrics:
  - accuracy
  - f1
title: IMDb Sentiment Analyzer
emoji: 🤗
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.29.0
app_file: app.py
pinned: false
hf_oauth: false
disable_embedding: false

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: [email protected]

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 is hosted on Hugging Face Spaces at voxmenthe/imdb-sentiment-demo. 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

Clone the repository (or your Space repository):

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

Install dependencies: Ensure you have Python 3.11+ installed.
```
pip install -r requirements.txt
```
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.