This model is a fine-tuned version of albert-base-v2 on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3608
  • Accuracy: 0.9138

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: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4.0

Training results

Framework versions

  • Transformers 4.9.1
  • Pytorch 1.9.0+cu102
  • Datasets 1.10.2
  • Tokenizers 0.10.3
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