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deberta-v3-large-finetuned-dagpap22-only-and-real

This model is a fine-tuned version of domenicrosati/deberta-v3-large-finetuned-dagpap22-only-and-real on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0008
  • F1: 0.9999
  • Precision: 1.0
  • Recall: 0.9997

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: 6e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Precision Recall
0.0016 1.0 10567 0.0060 0.9982 0.9997 0.9967
0.0 2.0 21134 0.0008 0.9999 1.0 0.9997

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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