README.md

metadata

language: en
license: apache-2.0
tags:
  - text-classification
  - sentiment-analysis
  - bert
  - imdb
datasets:
  - imdb
metrics:
  - accuracy
  - f1

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 😊