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ayesha9f/sentiment-tutorial

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face
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Model Card

sentiment-tutorial

Fine-tuned distilbert-base-uncased for binary sentiment classification.

Intended Use

Classify English text as positive or negative.

Training Procedure

  • Base model: distilbert-base-uncased
  • Epochs: 2
  • Learning rate: 2e-5
  • Batch size: 32
  • Max length: 128

Evaluation Results

Accuracy: 0.870

Precision: 0.879

Recall: 0.858

F1: 0.868

Limitations

  • Binary classification only
  • English only
  • Movie reviews domain

Usage

from transformers import pipeline

classifier = pipeline( "sentiment-analysis", model="ayesha9f/sentiment-tutorial" )

classifier("This was a great experience!")