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yes_no_qna_deberta_model

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

  • Loss: 0.5570
  • Accuracy: 0.8508

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.583 1.0 590 0.4086 0.8251
0.348 2.0 1180 0.4170 0.8465
0.2183 3.0 1770 0.5570 0.8508

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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Finetuned from

Dataset used to train nc33/yes_no_qna_deberta_model

Evaluation results