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bert_base_uncased

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

  • Loss: 0.5591
  • Accuracy: 0.8500

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: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 23 0.5552 0.8250
No log 2.0 46 0.4623 0.8250
No log 3.0 69 0.5304 0.8250
No log 4.0 92 0.5741 0.8500
No log 5.0 115 0.5591 0.8500

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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