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afaji/fine-tuned-IndoNLI-Translated-with-indobert-large-p2

sourceHugging Facemitupdated 4y agoView on Hugging Face
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fine-tuned-IndoNLI-Translated-with-indobert-large-p2

This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.6126
  • —Accuracy: 0.8090

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: 1e-05
  • —trainbatchsize: 64
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.06
  • —num_epochs: 16

Training results

Training LossEpochStepValidation LossAccuracy
0.5491.061360.53070.7896
0.4982.0122720.49080.8072
0.37043.0184080.50870.8105
0.31024.0245440.57080.8111
0.22265.0306800.64350.8053
0.16016.0368160.76760.8034
0.11337.0429520.81970.8083
0.10918.0490880.93840.8059
0.0669.0552241.03330.8066
0.05810.0613601.12110.8061
0.053911.0674961.22600.8080
0.035712.0736321.34700.8058
0.025613.0797681.44990.8079
0.028914.0859041.50780.8070
0.025915.0920401.58180.8078
0.019316.0981761.61260.8090

Framework versions

  • —Transformers 4.26.1
  • —Pytorch 1.13.1+cu117
  • —Datasets 2.2.0
  • —Tokenizers 0.13.2