🎬 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!"))
