HarshGahlaut/distilb-sentiment-best

DistilBERT Sentiment Classifier (Hybrid-Sentiment-Engine)

This model is a fine-tuned version of distilbert-base-uncased for binary sentiment classification (positive/negative).
It achieves approximately 90% F1 score on the IMDb dataset.

The model is part of the Hybrid-Sentiment-Engine, a project combining classical ML (TF-IDF + Logistic Regression) with transformer-based deep learning for flexible, high-accuracy sentiment analysis.

🔥 Model Details

• Base model: distilbert-base-uncased
• Task: Sentiment Analysis (binary)
• Dataset: IMDb reviews
• Languages: English
• Framework: Hugging Face Transformers
• License: MIT

📊 Performance

Metric	Score
F1 Score	~90%
Accuracy	~90%
Precision	~89%
Recall	~90%

📥 Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification

model_id = "HarshGahlaut/distilb-sentiment-best"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSequenceClassification.from_pretrained(model_id)