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bert-base-uncased-issues-128

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: 1.5503

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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 16
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.6214 1.0 291 2.2471
2.0594 2.0 582 1.9293
1.8563 3.0 873 1.7961
1.7442 4.0 1164 1.7518
1.657 5.0 1455 1.7390
1.577 6.0 1746 1.7173
1.5071 7.0 2037 1.6223
1.4661 8.0 2328 1.5691
1.4365 9.0 2619 1.6280
1.3827 10.0 2910 1.4641
1.3517 11.0 3201 1.6498
1.3294 12.0 3492 1.3006
1.2836 13.0 3783 1.6520
1.2867 14.0 4074 1.6064
1.2819 15.0 4365 1.4131
1.2611 16.0 4656 1.5503

Framework versions

  • Transformers 4.21.0
  • Pytorch 1.12.0+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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