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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: deberta-v3-large__sst2__train-8-9
    results: []

deberta-v3-large__sst2__train-8-9

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: 0.6013
  • Accuracy: 0.7210

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
0.6757 1.0 3 0.7810 0.25
0.6506 2.0 6 0.8102 0.25
0.6463 3.0 9 0.8313 0.25
0.5813 4.0 12 0.8858 0.25
0.4635 5.0 15 0.8220 0.25
0.3992 6.0 18 0.7226 0.5
0.3281 7.0 21 0.6707 0.75
0.2276 8.0 24 0.7515 0.75
0.1674 9.0 27 0.6971 0.75
0.0873 10.0 30 0.5419 0.75
0.0525 11.0 33 0.5025 0.75
0.0286 12.0 36 0.5229 0.75
0.0149 13.0 39 0.5660 0.75
0.0082 14.0 42 0.6954 0.75
0.006 15.0 45 0.8649 0.75
0.0043 16.0 48 1.0011 0.75
0.0035 17.0 51 1.0909 0.75
0.0021 18.0 54 1.1615 0.75
0.0017 19.0 57 1.2147 0.75
0.0013 20.0 60 1.2585 0.75
0.0016 21.0 63 1.2917 0.75

Framework versions

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