BERT Fine-tuned on IMDB Sentiment Analysis
Model Description
This model is a fine-tuned version of bert-base-uncased
on the IMDB movie reviews dataset for sentiment analysis.
Training Details
- Base Model: bert-base-uncased
- Dataset: IMDB (2000 train, 500 test samples)
- Epochs: 3
- Learning Rate: 2e-5
- Batch Size: 16
- Framework: HuggingFace Transformers
Results
| Metric | Score |
|---|---|
| Accuracy | ~88% |
| F1 Score | ~0.88 |
Usage
from transformers import pipeline
classifier = pipeline(
'sentiment-analysis',
model='your-hf-username/bert-imdb-sentiment'
)
result = classifier("This movie was absolutely amazing!")
print(result)
# [{'label': 'POSITIVE', 'score': 0.98}]
Labels
- LABEL_0 → Negative 😠
- LABEL_1 → Positive 😊