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afaji/fine-tuned-IndoNLI-Basic-with-xlm-roberta-large-LR-1e-05

sourceHugging Facemitupdated 4y agoView on Hugging Face
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fine-tuned-IndoNLI-Basic-with-xlm-roberta-large-LR-1e-05

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

  • —Loss: 0.9957
  • —Accuracy: 0.4479

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: 16
  • —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
1.12810.5801.13900.2918
1.12420.991601.10460.2918
1.12991.492401.11210.3409
1.11221.983201.09520.3673
1.11352.484001.10790.3673
1.11052.984801.11320.2918
1.05993.485601.05100.4706
1.05813.976401.02310.4998
1.00794.477200.99270.4492
1.0054.978000.99880.4479
1.00515.468800.99030.5198
1.00875.969600.98570.5175
1.01486.4610401.00940.4483
0.99696.9511200.99570.4479

Framework versions

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