bert-large-cased-finetuned-rte

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

  • Loss: 1.5187
  • Accuracy: 0.6643

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: 4
  • 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

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6969 1.0 623 0.7039 0.5343
0.5903 2.0 1246 0.6461 0.7184
0.4557 3.0 1869 1.5187 0.6643

Framework versions

  • Transformers 4.11.0.dev0
  • Pytorch 1.9.0
  • Datasets 1.12.1
  • Tokenizers 0.10.3
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Evaluation results