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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.

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Model size
109M params
Tensor type
F32
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Datasets used to train brianhuster/MRPC-bert