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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: fine-tuned-IndoNLI-Augmented-with-indobert-base-uncased
    results: []

fine-tuned-IndoNLI-Augmented-with-indobert-base-uncased

This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9276
  • Accuracy: 0.8014

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: 64
  • eval_batch_size: 16
  • seed: 42
  • 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
0.6316 1.0 6298 0.6317 0.7414
0.5501 2.0 12596 0.5378 0.7888
0.4978 3.0 18894 0.5407 0.7948
0.4193 4.0 25192 0.5259 0.8013
0.3766 5.0 31490 0.5447 0.8042
0.328 6.0 37788 0.5820 0.8023
0.2792 7.0 44086 0.6435 0.8012
0.261 8.0 50384 0.6578 0.8008
0.2071 9.0 56682 0.7064 0.8052
0.2004 10.0 62980 0.7446 0.8013
0.1657 11.0 69278 0.7735 0.8044
0.1729 12.0 75576 0.8078 0.8027
0.1399 13.0 81874 0.8660 0.8010
0.132 14.0 88172 0.8871 0.8006
0.1218 15.0 94470 0.9182 0.8001
0.1066 16.0 100768 0.9276 0.8014

Framework versions

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