stevhliu / my_awesome_swag_model

huggingface.co
Total runs: 5
24-hour runs: 0
7-day runs: 0
30-day runs: -4
Model's Last Updated: October 13 2022
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Introduction of my_awesome_swag_model

Model Details of my_awesome_swag_model

my_awesome_swag_model

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

  • Loss: 0.5192
  • Accuracy: 0.7981
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-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
0.6873 1.0 4597 0.5192 0.7981
Framework versions
  • Transformers 4.23.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.5.2
  • Tokenizers 0.13.1

Runs of stevhliu my_awesome_swag_model on huggingface.co

5
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0
24-hour runs
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3-day runs
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7-day runs
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30-day runs

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my_awesome_swag_model install

my_awesome_swag_model is an open source model from GitHub that offers a free installation service, and any user can find my_awesome_swag_model on GitHub to install. At the same time, huggingface.co provides the effect of my_awesome_swag_model install, users can directly use my_awesome_swag_model installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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stevhliu
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