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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
base_model: microsoft/deberta-v3-large
model-index:
  - name: deberta-v3-large__sst2__train-16-4
    results: []

deberta-v3-large__sst2__train-16-4

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: 0.6329
  • Accuracy: 0.6392

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
0.6945 1.0 7 0.7381 0.2857
0.7072 2.0 14 0.7465 0.2857
0.6548 3.0 21 0.7277 0.4286
0.5695 4.0 28 0.6738 0.5714
0.4615 5.0 35 0.8559 0.5714
0.0823 6.0 42 1.0983 0.5714
0.0274 7.0 49 1.9937 0.5714
0.0106 8.0 56 2.2209 0.5714
0.0039 9.0 63 2.2114 0.5714
0.0031 10.0 70 2.2808 0.5714
0.0013 11.0 77 2.3707 0.5714
0.0008 12.0 84 2.4902 0.5714
0.0005 13.0 91 2.5208 0.5714
0.0007 14.0 98 2.5683 0.5714

Framework versions

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