metadata
language: en
license: mit
datasets: imdb
tags:
- sentiment-analysis
- transformers
- huggingface
🎬 IMDb Sentiment Classifier
This is a fine-tuned DistilBERT model for analyzing sentiment in IMDb movie reviews.
📌 Dataset
- Source: IMDb dataset from Hugging Face Datasets
- Task: Binary classification (Positive / Negative)
📌 Training Details
- Model:
distilbert-base-uncased - Learning rate:
2e-5 - Batch size:
4 - Epochs:
1 - Loss function: CrossEntropyLoss
📌 Evaluation Results
| Metric | Score |
|---|---|
| Accuracy | 92.5% |
| F1-score | 92.6% |
| Precision | 92.9% |
| Recall | 92.3% |
📌 How to Use
from transformers import pipeline
classifier = pipeline("text-classification", model="Camilla9000/imdb-sentiment-classifier")
print(classifier("This movie was amazing!"))