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

  • Loss: 0.4103
  • Accuracy: 0.9175

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: 2.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3631 1.0 49088 0.3129 0.9130
0.2267 2.0 98176 0.4157 0.9153

Framework versions

  • Transformers 4.13.0.dev0
  • Pytorch 1.10.0
  • Datasets 1.15.2.dev0
  • Tokenizers 0.10.3
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Finetuned from

Space using NDugar/v3-Large-mnli 1