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

huggingface.co
Total runs: 23
24-hour runs: 0
7-day runs: -9
30-day runs: -134
Model's Last Updated: February 25 2023
text-classification

Introduction of fine-tuned-IndoNLI-Basic-with-indobert-large-p2

Model Details of fine-tuned-IndoNLI-Basic-with-indobert-large-p2

fine-tuned-IndoNLI-Basic-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: 1.2497
  • Accuracy: 0.7751
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
0.978 1.0 161 0.8505 0.6236
0.6752 2.0 322 0.6163 0.7542
0.5579 3.0 483 0.6259 0.7551
0.4328 4.0 644 0.6153 0.7706
0.3217 5.0 805 0.6348 0.7711
0.229 6.0 966 0.7245 0.7720
0.1688 7.0 1127 0.8032 0.7774
0.1258 8.0 1288 0.8898 0.7742
0.0942 9.0 1449 0.9629 0.7651
0.0718 10.0 1610 0.9848 0.7783
0.0635 11.0 1771 1.0794 0.7674
0.0407 12.0 1932 1.1378 0.7679
0.0394 13.0 2093 1.2195 0.7651
0.0323 14.0 2254 1.2151 0.7756
0.0235 15.0 2415 1.2509 0.7711
0.0277 16.0 2576 1.2497 0.7751
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-indobert-large-p2 on huggingface.co

23
Total runs
0
24-hour runs
-3
3-day runs
-9
7-day runs
-134
30-day runs

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