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Zidan_model_output_v2

This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7630
  • Accuracy: 0.6818

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-06
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 220 1.0479 0.5091
No log 2.0 440 0.9568 0.5455
1.0321 3.0 660 0.9094 0.5818
1.0321 4.0 880 0.8748 0.6182
0.8487 5.0 1100 0.8410 0.6182
0.8487 6.0 1320 0.8203 0.6727
0.7405 7.0 1540 0.8106 0.6273
0.7405 8.0 1760 0.7971 0.6636
0.7405 9.0 1980 0.7852 0.6636
0.6747 10.0 2200 0.7788 0.6636
0.6747 11.0 2420 0.7754 0.6455
0.6304 12.0 2640 0.7688 0.6545
0.6304 13.0 2860 0.7656 0.6727
0.6064 14.0 3080 0.7626 0.6727
0.6064 15.0 3300 0.7630 0.6818

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Model size
111M params
Tensor type
F32
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