deberta-v3-large__sst2__train-16-5

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: 0.5433
  • Accuracy: 0.7924

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
0.6774 1.0 7 0.7450 0.2857
0.7017 2.0 14 0.7552 0.2857
0.6438 3.0 21 0.7140 0.4286
0.3525 4.0 28 0.5570 0.7143
0.2061 5.0 35 0.5303 0.8571
0.0205 6.0 42 0.6706 0.8571
0.0068 7.0 49 0.8284 0.8571
0.0029 8.0 56 0.9281 0.8571
0.0015 9.0 63 0.9871 0.8571
0.0013 10.0 70 1.0208 0.8571
0.0008 11.0 77 1.0329 0.8571
0.0005 12.0 84 1.0348 0.8571
0.0004 13.0 91 1.0437 0.8571
0.0005 14.0 98 1.0512 0.8571
0.0004 15.0 105 1.0639 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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