---

language: en license: apache-2.0 tags:

• sentiment-analysis
• text-classification
• distilbert datasets:
• imdb metrics:
• accuracy
• f1 pipeline_tag: text-classification widget:
• text: "I absolutely loved this movie, it was amazing!"
• text: "This was the worst experience ever."

my-sentiment-analyzer

Fine-tuned DistilBERT model for sentiment analysis (positive / negative).

Training Data

IMDB dataset (25,000 train / 25,000 test)

Model Details

• Base model: distilbert-base-uncased
• Epochs: 2
• Learning rate: 2e-5
• Max length: 128

Evaluation Results

Metric	Score
Accuracy	0.874
Precision	0.864
Recall	0.888
F1	0.875

Limitations

• English only
• Binary classification only
• Movie-review domain only

Usage

from transformers import pipeline

classifier = pipeline( "sentiment-analysis", model="kashafEjaz50/my-sentiment-analyzer" )

print(classifier("This movie was fantastic!"))