optimum / roberta-large-finetuned-clinc

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Total runs: 13
24-hour runs: 0
7-day runs: 1
30-day runs: 6
Model's Last Updated: June 21 2023
text-classification

Introduction of roberta-large-finetuned-clinc

Model Details of roberta-large-finetuned-clinc

roberta-large-finetuned-clinc

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: 0.1574
  • Accuracy: 0.9729
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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
Training results
Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 239 0.8113 0.9035
No log 2.0 478 0.2364 0.9548
1.7328 3.0 717 0.1760 0.9684
1.7328 4.0 956 0.1565 0.9723
0.0976 5.0 1195 0.1574 0.9729
Framework versions
  • Transformers 4.11.3
  • Pytorch 1.11.0
  • Datasets 1.16.1
  • Tokenizers 0.10.3

Runs of optimum roberta-large-finetuned-clinc on huggingface.co

13
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3-day runs
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