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

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Total runs: 10
24-hour runs: 0
7-day runs: 1
30-day runs: -1
Model's Last Updated: February 25 2023
text-classification

Introduction of fine-tuned-IndoNLI-Basic-with-xlm-roberta-base

Model Details of fine-tuned-IndoNLI-Basic-with-xlm-roberta-base

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
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.06
  • num_epochs: 16
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.1127 1.0 161 1.1041 0.2918
1.1006 2.0 322 1.0960 0.3409
1.0368 3.0 483 1.0347 0.4201
0.9914 4.0 644 0.9819 0.4593
0.9718 5.0 805 1.0013 0.4297
0.9628 6.0 966 0.9786 0.4861
0.9565 7.0 1127 0.9940 0.5102
0.9418 8.0 1288 1.0082 0.4998
0.936 9.0 1449 1.0298 0.4574
0.9027 10.0 1610 1.0522 0.4770
0.8861 11.0 1771 1.0756 0.4665
0.9045 12.0 1932 1.0986 0.4488
0.8764 13.0 2093 1.0949 0.4315
0.8703 14.0 2254 1.1140 0.4729
0.8539 15.0 2415 1.1241 0.4511
0.8619 16.0 2576 1.1133 0.4665
Framework versions
  • Transformers 4.26.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.2.0
  • Tokenizers 0.13.2

Runs of afaji fine-tuned-IndoNLI-Basic-with-xlm-roberta-base on huggingface.co

10
Total runs
0
24-hour runs
2
3-day runs
1
7-day runs
-1
30-day runs

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