shadowdemonosprey/mrpc-distilbert

DistilBERT MRPC Paraphrase Classifier

Fine-tuned distilbert-base-uncased model for paraphrase identification using the GLUE MRPC dataset.

Model Description

This model predicts whether two sentences have the same meaning.

Labels

• 0 → NOT_PARAPHRASE
• 1 → PARAPHRASE

Dataset

• Dataset: GLUE MRPC
• Task: Sentence pair classification

Training Details

• Base model: distilbert-base-uncased
• Epochs: 1
• Batch size: 8
• Maximum sequence length: 128

Evaluation

Accuracy: 85.05%

Usage

Use the model with Hugging Face Transformers:

from transformers import pipeline

classifier = pipeline( "text-classification", model="shadowdemonosprey/mrpc-distilbert" )

result = classifier( { "text": "The company released a new phone.", "text_pair": "A new phone was released by the company." } )

print(result)

Example Output

PARAPHRASE
Confidence: 0.9643

Limitations

This model was trained on the MRPC dataset and may not generalize perfectly to all sentence similarity tasks.