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test-trainer-glue-mrpc

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: 0.6850
  • Accuracy: {'accuracy': 0.8627450980392157}
  • F1: 0.9024

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: 5e-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: 3.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.0 459 0.3762 {'accuracy': 0.8455882352941176} 0.8873
0.4903 2.0 918 0.5500 {'accuracy': 0.8431372549019608} 0.8923
0.2654 3.0 1377 0.6850 {'accuracy': 0.8627450980392157} 0.9024

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Inference API
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Dataset used to train P3ps/test-trainer-glue-mrpc

Evaluation results