Hugging-GK/ModerBert-MultiClass-IMDB-imdb_complete_data

ModernBERT Fine-tuned for IMDB Sentiment Analysis

This model is a fine-tuned version of answerdotai/ModernBERT-base for sentiment analysis on the IMDB movie review dataset.

Dataset

The model was fine-tuned on a subset of the IMDB dataset.

• Training Split Size: 5000 samples
• Validation Split Size: 12500 samples
• Test Split Size: 1000 samples

Evaluation Results

The model was evaluated on the validation set after training. The key metrics are:

• Validation Loss: 0.1587
• Validation Accuracy: 0.9478
• Validation F1-score (macro): 0.9488

The best model checkpoint was saved at step 300.

Usage

You can use this model for text classification (sentiment analysis) using the Hugging Face pipeline:

from transformers import pipeline

model_id = "Hugging-GK/ModerBert-MultiClass-IMDB-imdb_complete_data"
sentiment_pipeline = pipeline("text-classification", model=model_id)

text = "This movie was fantastic!"
result = sentiment_pipeline(text)
print(result)

text = "This movie was terrible."
result = sentiment_pipeline(text)
print(result)

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Model Details

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