gokuls / hBERTv1_wnli

huggingface.co
Total runs: 14
24-hour runs: 0
7-day runs: -3
30-day runs: -3
Model's Last Updated: March 02 2023
text-classification

Introduction of hBERTv1_wnli

Model Details of hBERTv1_wnli

hBERTv1_wnli

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6877
  • Accuracy: 0.5634
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: 256
  • eval_batch_size: 256
  • seed: 10
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.7359 1.0 3 0.7194 0.4366
0.6989 2.0 6 0.6899 0.5634
0.7031 3.0 9 0.7028 0.4366
0.7012 4.0 12 0.6889 0.5634
0.697 5.0 15 0.6894 0.5634
0.6971 6.0 18 0.7015 0.4366
0.7 7.0 21 0.6882 0.5634
0.6928 8.0 24 0.6890 0.5634
0.6932 9.0 27 0.6897 0.5634
0.6954 10.0 30 0.6956 0.4366
0.6962 11.0 33 0.6913 0.5634
0.6956 12.0 36 0.6877 0.5634
0.6973 13.0 39 0.6926 0.5070
0.6978 14.0 42 0.6933 0.4930
0.6945 15.0 45 0.6883 0.5634
0.6974 16.0 48 0.6881 0.5634
0.6936 17.0 51 0.6925 0.5211
Framework versions
  • Transformers 4.26.1
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.10.1
  • Tokenizers 0.13.2

Runs of gokuls hBERTv1_wnli on huggingface.co

14
Total runs
0
24-hour runs
2
3-day runs
-3
7-day runs
-3
30-day runs

More Information About hBERTv1_wnli huggingface.co Model

hBERTv1_wnli huggingface.co

hBERTv1_wnli huggingface.co is an AI model on huggingface.co that provides hBERTv1_wnli's model effect (), which can be used instantly with this gokuls hBERTv1_wnli model. huggingface.co supports a free trial of the hBERTv1_wnli model, and also provides paid use of the hBERTv1_wnli. Support call hBERTv1_wnli model through api, including Node.js, Python, http.

hBERTv1_wnli huggingface.co Url

https://huggingface.co/gokuls/hBERTv1_wnli

gokuls hBERTv1_wnli online free

hBERTv1_wnli huggingface.co is an online trial and call api platform, which integrates hBERTv1_wnli's modeling effects, including api services, and provides a free online trial of hBERTv1_wnli, you can try hBERTv1_wnli online for free by clicking the link below.

gokuls hBERTv1_wnli online free url in huggingface.co:

https://huggingface.co/gokuls/hBERTv1_wnli

hBERTv1_wnli install

hBERTv1_wnli is an open source model from GitHub that offers a free installation service, and any user can find hBERTv1_wnli on GitHub to install. At the same time, huggingface.co provides the effect of hBERTv1_wnli install, users can directly use hBERTv1_wnli installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

hBERTv1_wnli install url in huggingface.co:

https://huggingface.co/gokuls/hBERTv1_wnli

Url of hBERTv1_wnli

hBERTv1_wnli huggingface.co Url

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