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