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Add evaluation results on the adversarialQA config and validation split of adversarial_qa
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - squad
model-index:
  - name: bert-finetuned-squad
    results:
      - task:
          type: question-answering
          name: Question Answering
        dataset:
          name: adversarial_qa
          type: adversarial_qa
          config: adversarialQA
          split: validation
        metrics:
          - type: f1
            value: 30.1868
            name: F1
            verified: true
            verifyToken: >-
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          - type: exact_match
            value: 19.7667
            name: Exact Match
            verified: true
            verifyToken: >-
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          - type: loss
            value: 3.1052029132843018
            name: loss
            verified: true
            verifyToken: >-
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bert-finetuned-squad

This model is a fine-tuned version of bert-base-cased on the squad dataset.

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Framework versions

  • Transformers 4.27.4
  • Pytorch 1.13.1+cu116
  • Datasets 2.11.0
  • Tokenizers 0.13.2