deberta-v3-large__sst2__train-16-0

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: 0.9917
  • Accuracy: 0.7705

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
0.7001 1.0 7 0.7327 0.2857
0.6326 2.0 14 0.6479 0.5714
0.5232 3.0 21 0.5714 0.5714
0.3313 4.0 28 0.6340 0.7143
0.3161 5.0 35 0.6304 0.7143
0.0943 6.0 42 0.4719 0.8571
0.0593 7.0 49 0.5000 0.7143
0.0402 8.0 56 0.3530 0.8571
0.0307 9.0 63 0.3499 0.8571
0.0033 10.0 70 0.3258 0.8571
0.0021 11.0 77 0.3362 0.8571
0.0012 12.0 84 0.4591 0.8571
0.0036 13.0 91 0.4661 0.8571
0.001 14.0 98 0.5084 0.8571
0.0017 15.0 105 0.5844 0.8571
0.0005 16.0 112 0.6645 0.8571
0.002 17.0 119 0.7422 0.8571
0.0006 18.0 126 0.7354 0.8571
0.0005 19.0 133 0.7265 0.8571
0.0005 20.0 140 0.7207 0.8571

Framework versions

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