bert-base-uncased-finetuned-swag

This model is a fine-tuned version of bert-base-uncased on the swag dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7187
  • Accuracy: 0.7223

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: 32
  • eval_batch_size: 32
  • 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
0.9645 1.0 2299 0.7779 0.6998
0.8942 2.0 4598 0.7322 0.7184
0.8907 3.0 6897 0.7187 0.7223

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.1.0
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train NightMachinery/bert-base-uncased-finetuned-swag