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mrpc-distilbert
shadowdemonosprey/mrpc-distilbert
mrpc-distilbert is a text classification model from shadowdemonosprey. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
Fine-tuned distilbert-base-uncased model for paraphrase identification using the GLUE MRPC dataset.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 11, 2026
- Updated
- Aug 11, 2026
- SHA
- f3f92d6f
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Model card
From the Hugging Face model README
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_PARAPHRASE1→ 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.
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Languages
- en
- Created
- Aug 11, 2026
- Updated
- Aug 11, 2026