bert-base-uncased-finetuned-swag

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

  • Loss: 1.0986
  • Accuracy: 0.3642

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: 2
  • eval_batch_size: 2
  • 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
1.1039 1.0 3058 1.0983 0.3779
1.0995 2.0 6116 1.0986 0.3544
1.1029 3.0 9174 1.0986 0.3642

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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Dataset used to train SuryaaSeran/bert-base-uncased-finetuned-swag