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Bert-test-model

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

  • Loss: 1.3708

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: 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: 3

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 250 1.7369
2.2639 2.0 500 1.3940
2.2639 3.0 750 1.3708

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train Jellevdl/Bert-test-model