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This model is a fine-tuned version of roberta-large on the clinc_oos dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1692

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
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss
0.3719 1.0 954 0.3159
0.0131 2.0 1908 0.1692
0.0149 3.0 2862 0.1947
0.0179 4.0 3816 0.1907
0.04 5.0 4770 0.1877
0.001 6.0 5724 0.1908
0.0473 7.0 6678 0.1961
0.0007 8.0 7632 0.1960
0.0415 9.0 8586 0.1945
0.0005 10.0 9540 0.1971

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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Dataset used to train MRUNLLM/clinic_oos_finetuned_roberta_model