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bert-sentiment-analysis-model
Harsha901/bert-sentiment-analysis-model
bert-sentiment-analysis-model is a text classification model from Harsha901. Use it when you need a label for a piece of text. The card lists the license as mit.
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 Transfor…
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At a glance
- Task
- Text Classification
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jun 2, 2025
- Updated
- Aug 5, 2025
- SHA
- b7b3cf53
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Model card
From the Hugging Face model README
📊 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!")
- Task
- Text Classification
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Jun 2, 2025
- Updated
- Aug 5, 2025