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baseline-ft-mrpc-IRoberta-b-8bit

This model is a fine-tuned version of vuiseng9/baseline-ft-mrpc-IRoberta-b-unquantized on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3871
  • Accuracy: 0.8971
  • F1: 0.9258
  • Combined Score: 0.9114

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-07
  • 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: 12.0

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Combined Score
0.0021 1.0 230 0.4017 0.8848 0.9147 0.8998
0.0026 2.0 460 0.4105 0.8873 0.9173 0.9023
0.0026 3.0 690 0.3707 0.8946 0.9236 0.9091
0.0037 4.0 920 0.3893 0.8946 0.9228 0.9087
1.324 5.0 1150 0.3871 0.8897 0.9204 0.9050
0.0227 6.0 1380 0.3951 0.8897 0.9201 0.9049
0.0081 7.0 1610 0.3818 0.8824 0.9155 0.8989
0.0054 8.0 1840 0.3902 0.8873 0.9181 0.9027
0.0383 9.0 2070 0.3659 0.8922 0.9225 0.9073
0.3861 10.0 2300 0.4260 0.8652 0.9030 0.8841
0.0028 11.0 2530 0.3619 0.8946 0.9234 0.9090
0.0957 12.0 2760 0.3871 0.8971 0.9258 0.9114

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3
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Dataset used to train vuiseng9/baseline-ft-mrpc-IRoberta-b-8bit

Evaluation results