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testing

This model is a fine-tuned version of distilbert-base-uncased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6644
  • Accuracy: 0.6814
  • F1: 0.8105
  • Combined Score: 0.7459

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: 2e-05
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 10

Training results

Framework versions

  • Transformers 4.11.0.dev0
  • Pytorch 1.9.0+cu111
  • Datasets 1.11.0
  • Tokenizers 0.10.3
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Dataset used to train LysandreJik/testing

Evaluation results