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deberta-v3-large-finetuned-paws-paraphrase-detector

Feel free to use for paraphrase detection tasks!

This model is a fine-tuned version of microsoft/deberta-v3-large on the paws dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3046
  • F1: 0.9427
  • Precision: 0.9301
  • Recall: 0.9556

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 6e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Precision Recall
0.1492 1.0 6176 0.1650 0.9537 0.9385 0.9695
0.1018 2.0 12352 0.1968 0.9544 0.9427 0.9664
0.0482 3.0 18528 0.2419 0.9521 0.9388 0.9658

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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Dataset used to train domenicrosati/deberta-v3-large-finetuned-paws-paraphrase-detector

Evaluation results