autoevaluate / binary-classification-not-evaluated

huggingface.co
Total runs: 10
24-hour runs: 0
7-day runs: 2
30-day runs: 4
Model's Last Updated: November 29 2022
text-classification

Introduction of binary-classification-not-evaluated

Model Details of binary-classification-not-evaluated

binary-classification

This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3009
  • Accuracy: 0.8968
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
  • num_epochs: 1
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.175 1.0 4210 0.3009 0.8968
Framework versions
  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1

Runs of autoevaluate binary-classification-not-evaluated on huggingface.co

10
Total runs
0
24-hour runs
2
3-day runs
2
7-day runs
4
30-day runs

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