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push-to-hub-test-2

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

  • Loss: 0.6255
  • Accuracy: 0.8676
  • F1: 0.9078
  • Combined Score: 0.8877

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: 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: 3.0

Training results

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.0+cu117
  • Datasets 2.14.4.dev0
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train sgugger/push-to-hub-test-2

Evaluation results