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afaji/fine-tuned-IndoNLI-Translated-with-xlm-roberta-base

sourceHugging Facemitupdated 4y agoView on Hugging Face
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Model Card

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fine-tuned-IndoNLI-Translated-with-xlm-roberta-base

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.8557
  • —Accuracy: 0.6567

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: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 64
  • —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
0.99321.061360.98780.5004
0.97422.0122720.93400.5507
0.90433.0184080.90580.5694
0.87264.0245440.89180.5840
0.86515.0306800.86480.6017
0.8226.0368160.83790.6253
0.78687.0429520.83690.6299
0.78218.0490880.82190.6410
0.73099.0552240.82540.6465
0.734410.0613600.81360.6479
0.717311.0674960.82410.6532
0.717712.0736320.81200.6536
0.664613.0797680.84200.6570
0.653314.0859040.84490.6546
0.65615.0920400.84950.6554
0.634516.0981760.85570.6567

Framework versions

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