gokuls / bert-uncased-massive-intent-classification

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Total runs: 10
24-hour runs: 0
7-day runs: -3
30-day runs: -9
Model's Last Updated: September 19 2022
text-classification

Introduction of bert-uncased-massive-intent-classification

Model Details of bert-uncased-massive-intent-classification

bert-uncased-massive-intent-classification

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

  • Loss: 0.8396
  • Accuracy: 0.8854
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: 33
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.4984 1.0 720 0.6402 0.8495
0.4376 2.0 1440 0.5394 0.8731
0.2318 3.0 2160 0.5903 0.8760
0.1414 4.0 2880 0.6221 0.8805
0.087 5.0 3600 0.7072 0.8819
0.0622 6.0 4320 0.7121 0.8819
0.036 7.0 5040 0.7750 0.8805
0.0234 8.0 5760 0.7767 0.8834
0.0157 9.0 6480 0.8243 0.8805
0.0122 10.0 7200 0.8198 0.8839
0.0092 11.0 7920 0.8105 0.8849
0.0047 12.0 8640 0.8561 0.8844
0.0038 13.0 9360 0.8367 0.8815
0.0029 14.0 10080 0.8396 0.8854
0.0014 15.0 10800 0.8410 0.8849
Framework versions
  • Transformers 4.22.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1

Runs of gokuls bert-uncased-massive-intent-classification on huggingface.co

10
Total runs
0
24-hour runs
0
3-day runs
-3
7-day runs
-9
30-day runs

More Information About bert-uncased-massive-intent-classification huggingface.co Model

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bert-uncased-massive-intent-classification huggingface.co

bert-uncased-massive-intent-classification huggingface.co is an AI model on huggingface.co that provides bert-uncased-massive-intent-classification's model effect (), which can be used instantly with this gokuls bert-uncased-massive-intent-classification model. huggingface.co supports a free trial of the bert-uncased-massive-intent-classification model, and also provides paid use of the bert-uncased-massive-intent-classification. Support call bert-uncased-massive-intent-classification model through api, including Node.js, Python, http.

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https://huggingface.co/gokuls/bert-uncased-massive-intent-classification

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bert-uncased-massive-intent-classification install

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

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