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deberta-v3-large__sst2__train-32-1

This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4201
  • Accuracy: 0.8759

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7162 1.0 13 0.6832 0.5385
0.6561 2.0 26 0.7270 0.4615
0.4685 3.0 39 1.0674 0.5385
0.2837 4.0 52 1.0841 0.5385
0.1129 5.0 65 0.3502 0.9231
0.0118 6.0 78 0.4829 0.9231
0.0022 7.0 91 0.7430 0.8462
0.0007 8.0 104 0.8219 0.8462
0.0005 9.0 117 0.8787 0.8462
0.0003 10.0 130 0.8713 0.8462
0.0003 11.0 143 0.8473 0.8462
0.0002 12.0 156 0.8482 0.8462
0.0002 13.0 169 0.8494 0.8462
0.0002 14.0 182 0.8638 0.8462
0.0002 15.0 195 0.8492 0.8462

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2
  • Tokenizers 0.10.3
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