bert-base-uncased-finetuned-swag-e1-b16-l5e5

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: 0.5202
  • Accuracy: 0.7997

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: 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: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.701 1.0 4597 0.5202 0.7997

Framework versions

  • Transformers 4.12.2
  • Pytorch 1.9.1
  • Datasets 1.12.1
  • Tokenizers 0.10.3
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Dataset used to train JazibEijaz/bert-base-uncased-finetuned-swag-e1-b16-l5e5

Evaluation results