Harsha901/bert-sentiment-analysis-model

📊 Sentiment Analysis with Fine-Tuned BERT (IMDB)

This repository contains a fine-tuned BERT model for binary sentiment classification using the IMDB movie reviews dataset. The model classifies reviews as positive or negative, and is built using Hugging Face Transformers and PyTorch.

🚀 Model Performance

Metric	Value
Accuracy	89.4%
Validation Loss	0.375
Epochs Trained	3
Inference Speed	~434 samples/sec

🧠 Model Details

• Base Model: bert-base-uncased
• Dataset: IMDB (binary sentiment)
• Framework: Hugging Face Transformers
• Fine-Tuning Setup:
  • Learning rate: 2e-5
  • Batch size: 32
  • Mixed-precision: ✅ (fp16)
  • Early stopping: ❌ (trained for full 3 epochs)

🛠️ How to Use

from transformers import pipeline

classifier = pipeline("text-classification", model="Harsha901/tinybert-imdb-sentiment-analysis-model")
classifier("This movie was absolutely amazing!")