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pert-qa

This model is a fine-tuned version of hfl/chinese-pert-large on the cmrc2018 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6942

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss
1.1273 1.0 1200 0.7088
0.6132 2.0 2400 0.6942

Framework versions

  • Transformers 4.23.1
  • Pytorch 1.10.0+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.1
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Dataset used to train cgt/pert-qa