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bert-base-multilingual-cased-vnrte-10

This model is a fine-tuned version of bert-base-multilingual-cased on the tmnam20/VieGLUE/VNRTE dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0005
  • Accuracy: 0.9997

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: 32
  • eval_batch_size: 16
  • seed: 10
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0044 1.28 500 0.0083 0.9978
0.0001 2.55 1000 0.0026 0.9994

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.2.0.dev20231203+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Evaluation results