deberta-v3-large__sst2__train-8-6

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: 1.4331
  • Accuracy: 0.7106

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
0.6486 1.0 3 0.7901 0.25
0.6418 2.0 6 0.9259 0.25
0.6169 3.0 9 1.0574 0.25
0.5639 4.0 12 1.1372 0.25
0.4562 5.0 15 0.6090 0.5
0.3105 6.0 18 0.4435 1.0
0.2303 7.0 21 0.2804 1.0
0.1388 8.0 24 0.2205 1.0
0.0918 9.0 27 0.1282 1.0
0.0447 10.0 30 0.0643 1.0
0.0297 11.0 33 0.0361 1.0
0.0159 12.0 36 0.0211 1.0
0.0102 13.0 39 0.0155 1.0
0.0061 14.0 42 0.0158 1.0
0.0049 15.0 45 0.0189 1.0
0.0035 16.0 48 0.0254 1.0
0.0027 17.0 51 0.0305 1.0
0.0021 18.0 54 0.0287 1.0
0.0016 19.0 57 0.0215 1.0
0.0016 20.0 60 0.0163 1.0
0.0014 21.0 63 0.0138 1.0
0.0015 22.0 66 0.0131 1.0
0.001 23.0 69 0.0132 1.0
0.0014 24.0 72 0.0126 1.0
0.0011 25.0 75 0.0125 1.0
0.001 26.0 78 0.0119 1.0
0.0008 27.0 81 0.0110 1.0
0.0007 28.0 84 0.0106 1.0
0.0008 29.0 87 0.0095 1.0
0.0009 30.0 90 0.0089 1.0
0.0008 31.0 93 0.0083 1.0
0.0007 32.0 96 0.0075 1.0
0.0008 33.0 99 0.0066 1.0
0.0006 34.0 102 0.0059 1.0
0.0007 35.0 105 0.0054 1.0
0.0008 36.0 108 0.0051 1.0
0.0007 37.0 111 0.0049 1.0
0.0007 38.0 114 0.0047 1.0
0.0006 39.0 117 0.0045 1.0
0.0006 40.0 120 0.0046 1.0
0.0005 41.0 123 0.0045 1.0
0.0006 42.0 126 0.0044 1.0
0.0006 43.0 129 0.0043 1.0
0.0006 44.0 132 0.0044 1.0
0.0005 45.0 135 0.0045 1.0
0.0006 46.0 138 0.0043 1.0
0.0006 47.0 141 0.0043 1.0
0.0006 48.0 144 0.0041 1.0
0.0007 49.0 147 0.0042 1.0
0.0005 50.0 150 0.0042 1.0

Framework versions

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