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BERT_QandA

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

  • Loss: 0.4298
  • Accuracy: 0.8765

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: 3e-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
0.5797 1.0 619 0.4172 0.8532
0.3531 2.0 1238 0.3885 0.8735
0.2334 3.0 1857 0.4298 0.8765

Framework versions

  • Transformers 4.26.1
  • Pytorch 2.0.0.dev20230220
  • Datasets 2.10.0
  • Tokenizers 0.11.0
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Dataset used to train mhr2004/BERT_QandA

Evaluation results