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bert-large-cased-bn-adapter-3.17M-snli-model3

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

  • Loss: 0.7627
  • Accuracy: 0.7315

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: 64
  • eval_batch_size: 64
  • seed: 61
  • 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
0.4101 1.0 8584 0.3392 0.8718
0.3707 2.0 17168 0.3116 0.8842
0.3628 3.0 25752 0.3035 0.8879

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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