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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: bert-base-uncased-finetuned-qnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: qnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.791689547867472

bert-base-uncased-finetuned-qnli

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

  • Loss: 0.6268
  • Accuracy: 0.7917

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: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 63 0.5339 0.7620
No log 2.0 126 0.4728 0.7866
No log 3.0 189 0.5386 0.7847
No log 4.0 252 0.6096 0.7904
No log 5.0 315 0.6268 0.7917

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.1
  • Tokenizers 0.10.3