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deberta-v3-large-finetuned-synthetic-translated-only

This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0005
  • F1: 0.9961
  • Precision: 1.0
  • Recall: 0.9922

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: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Precision Recall
0.0065 1.0 10158 0.0022 0.9887 0.9962 0.9813
0.0006 2.0 20316 0.0030 0.9887 0.9962 0.9813
0.0008 3.0 30474 0.0029 0.9906 0.9962 0.9851

Framework versions

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