SetFit / deberta-v3-large__sst2__train-8-2

huggingface.co
Total runs: 33
24-hour runs: 1
7-day runs: 6
30-day runs: 31
Model's Last Updated: February 10 2022
text-classification

Introduction of deberta-v3-large__sst2__train-8-2

Model Details of deberta-v3-large__sst2__train-8-2

deberta-v3-large__sst2__train-8-2

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: 0.6794
  • Accuracy: 0.6063
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
0.6942 1.0 3 0.7940 0.25
0.6068 2.0 6 0.9326 0.25
0.6553 3.0 9 0.7979 0.25
0.475 4.0 12 0.7775 0.25
0.377 5.0 15 0.7477 0.25
0.3176 6.0 18 0.6856 0.75
0.2708 7.0 21 0.6554 0.75
0.2855 8.0 24 0.8129 0.5
0.148 9.0 27 0.7074 0.75
0.0947 10.0 30 0.7090 0.75
0.049 11.0 33 0.7885 0.75
0.0252 12.0 36 0.9203 0.75
0.0165 13.0 39 1.0937 0.75
0.0084 14.0 42 1.2502 0.75
0.0059 15.0 45 1.3726 0.75
0.0037 16.0 48 1.4784 0.75
0.003 17.0 51 1.5615 0.75
Framework versions
  • Transformers 4.15.0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2
  • Tokenizers 0.10.3

Runs of SetFit deberta-v3-large__sst2__train-8-2 on huggingface.co

33
Total runs
1
24-hour runs
3
3-day runs
6
7-day runs
31
30-day runs

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