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test_model

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0749
  • Accuracy: 0.9720
  • F1: 0.9698
  • Precision: 0.9710
  • Recall: 0.9720

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.0812 1.0 1315 0.0749 0.9720 0.9698 0.9710 0.9720

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.10.2
  • Datasets 2.2.2
  • Tokenizers 0.12.1
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Inference API
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