distilbert-imdb-sentiment – AI Model by imrankhan11 | AlphaNeural AI

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imrankhan11/
distilbert-imdb-sentiment

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text-classification

sentiment-analysis

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DistilBERT IMDb Sentiment Classifier

A fine-tuned DistilBERT model for binary sentiment analysis on movie reviews.

Model Description

Fine-tuned from distilbert-base-uncased on 5,000 IMDb movie reviews for 3 epochs. Classifies text as POSITIVE or NEGATIVE sentiment.

Training Data

Source: IMDb Large Movie Review Dataset
Train: 5,000 samples | Validation: 1,000 samples
Label balance: approximately 50% positive, 50% negative

Evaluation Results

Metric	Score
Accuracy	89.4%
F1 Score	0.894

Baseline Comparison

Model	Accuracy
TF-IDF + Logistic Regression	89.4%
DistilBERT (this model)	89.4%

How to Use

python

from transformers import pipeline
classifier = pipeline('text-classification', model='imrankhan11/distilbert-imdb-sentiment')
result = classifier('This movie was absolutely incredible!')
# Output: [{'label': 'POSITIVE', 'score': 0.997}]

Limitations

Trained only on English movie reviews — other domains may vary
May not handle Urdu, Roman Urdu, or code-switched text well
Sarcasm may be misclassified