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bert-large-cased-finetuned-low20-1-cased-DA-20

This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0643

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.5949 1.0 1 2.1115
2.0432 2.0 2 1.1308
1.8673 3.0 3 2.9839
2.148 4.0 4 3.1041
2.3452 5.0 5 0.8330
2.7264 6.0 6 0.4304
2.2264 7.0 7 0.7261
1.7837 8.0 8 2.6532
2.1499 9.0 9 1.0848
1.8867 10.0 10 1.6630
2.1755 11.0 11 0.9400
2.3771 12.0 12 2.6569
1.9036 13.0 13 2.8530
2.6166 14.0 14 0.5954
2.568 15.0 15 2.6136
2.5912 16.0 16 2.6986
1.245 17.0 17 2.1147
2.1394 18.0 18 1.0086
1.6254 19.0 19 2.1770
1.9212 20.0 20 1.0643

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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