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Bert_QA_multiple_choice

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

  • Loss: 1.3867
  • Accuracy: 0.6017

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: 8
  • eval_batch_size: 8
  • 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
1.1769 1.0 752 1.0007 0.5736
0.7735 2.0 1504 0.9846 0.5977
0.3761 3.0 2256 1.3867 0.6017

Framework versions

  • Transformers 4.36.0
  • Pytorch 2.1.1+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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