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BERT_BOOLQ_Circa_YN

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metadata
tags:
  - generated_from_trainer
datasets:
  - circa
metrics:
  - accuracy
model-index:
  - name: BERT_BOOLQ_Circa_YN
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: circa
          type: circa
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9090771328989241

BERT_BOOLQ_Circa_YN

This model is a fine-tuned version of lewtun/bert-large-uncased-wwm-finetuned-boolq on the circa dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3944
  • Accuracy: 0.9091

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
0.5055 1.0 619 0.3336 0.8868
0.2832 2.0 1238 0.3039 0.9100
0.1729 3.0 1857 0.3944 0.9091

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2