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yn_answer

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7690
  • Accuracy: 0.8519

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: 5e-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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4858 1.0 631 0.3401 0.8555
0.2667 2.0 1262 0.4624 0.8447
0.1424 3.0 1893 0.7690 0.8519

Framework versions

  • Transformers 4.34.0
  • Pytorch 1.13.0a0+git6c9b55e
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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