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bert-small-unidic-bpe2

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

  • Loss: 1.5665
  • Accuracy: 0.6690

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: 0.0001
  • train_batch_size: 768
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.01
  • num_epochs: 14
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.111 1.0 69473 1.9831 0.6056
1.9667 2.0 138946 1.8334 0.6277
1.8918 3.0 208419 1.7656 0.6376
1.8518 4.0 277892 1.7219 0.6444
1.8202 5.0 347365 1.6904 0.6490
1.7996 6.0 416838 1.6705 0.6524
1.7767 7.0 486311 1.6479 0.6558
1.7663 8.0 555784 1.6339 0.6577
1.7524 9.0 625257 1.6159 0.6611
1.7398 10.0 694730 1.6020 0.6627
1.7229 11.0 764203 1.5920 0.6645
1.7127 12.0 833676 1.5836 0.6658
1.7011 13.0 903149 1.5737 0.6677
1.7 14.0 972622 1.5665 0.6690

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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