---

MRPC-bert

This model is a fine-tuned version of bert-base-uncased on the GLUE MRPC dataset.

Training hyperparameters

The following hyperparameters were used during training:

• num_epochs: 3

Framework versions

• Transformers 4.38.0.dev0
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.0

#Running model with Python

from transformers import pipeline

classifier = pipeline("text-classification", model="brianhuster/MRPC-bert")
classifier(
    "Sentence 1. Sentence 2."
)

Replace "Sentence 1" and "Sentence 2" with your actual input sentence. Each sentence should end with a fullstop, even if they are questions. The model will return LABEL_1 if they are are equivalent in meaning, LABEL_1 otherwise.