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

sourceHugging Facemitupdated 4y agoView on Hugging Face
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fine-tuned-IndoNLI-Basic-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: 1.1133
  • —Accuracy: 0.4665

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
1.11271.01611.10410.2918
1.10062.03221.09600.3409
1.03683.04831.03470.4201
0.99144.06440.98190.4593
0.97185.08051.00130.4297
0.96286.09660.97860.4861
0.95657.011270.99400.5102
0.94188.012881.00820.4998
0.9369.014491.02980.4574
0.902710.016101.05220.4770
0.886111.017711.07560.4665
0.904512.019321.09860.4488
0.876413.020931.09490.4315
0.870314.022541.11400.4729
0.853915.024151.12410.4511
0.861916.025761.11330.4665

Framework versions

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