dcarpintero / bert-mrpc-finetuned

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Model's Last Updated: August 16 2024

Introduction of bert-mrpc-finetuned

Model Details of bert-mrpc-finetuned

Model description

Fine-tuned version of bert-base-uncased on the Microsoft Research Paraphrase Corpus (MRPC) dataset for paraphrase detection using the MRPC dataset.

Intended uses & limitations

This model is intended for paraphrase detection tasks, particularly those similar to the MRPC dataset. It may not perform well on substantially different datasets or tasks.

Training and evaluation data

The model was trained on the MRPC dataset, which contains 5,801 sentence pairs extracted from news sources on the web. 3,900 pairs were labeled as paraphrases by human annotators.

Training procedure

The model was fine-tuned using the Hugging Face Transformers library. We used a batch size of 16, learning rate of 2e-5, and trained for 3 epochs.

Evaluation results

The model achieved the following results on the MRPC validation set:

  • Accuracy: 0.8480
  • F1 Score: 0.8927

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bert-mrpc-finetuned huggingface.co is an AI model on huggingface.co that provides bert-mrpc-finetuned's model effect (), which can be used instantly with this dcarpintero bert-mrpc-finetuned model. huggingface.co supports a free trial of the bert-mrpc-finetuned model, and also provides paid use of the bert-mrpc-finetuned. Support call bert-mrpc-finetuned model through api, including Node.js, Python, http.

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