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Labira
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LabiraPJOK_1_500

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Transformers
TensorFlow
bert
generated_from_keras_callback
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LabiraPJOK_1_500 / README.md
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metadata
library_name: transformers
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: Labira/LabiraPJOK_1_500
    results: []

Labira/LabiraPJOK_1_500

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:

  • Train Loss: 0.0003
  • Validation Loss: 9.4417
  • Epoch: 60

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:

  • optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1500, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Epoch
0.0054 8.3302 0
0.0108 7.8442 1
0.0114 7.0958 2
0.0284 6.6490 3
0.0179 7.3034 4
0.0044 8.1785 5
0.0070 8.4039 6
0.0038 8.2728 7
0.0028 8.1154 8
0.0140 8.1207 9
0.0160 8.1384 10
0.0029 8.2978 11
0.0112 8.6940 12
0.0100 8.7433 13
0.0062 8.6486 14
0.0059 8.4821 15
0.0055 8.4559 16
0.0039 8.5136 17
0.0044 8.2783 18
0.0016 8.0974 19
0.0094 7.9739 20
0.0020 8.2513 21
0.0008 8.4637 22
0.0039 8.2813 23
0.0017 8.2027 24
0.0018 8.2722 25
0.0015 8.3875 26
0.0013 8.4975 27
0.0013 8.6171 28
0.0009 8.7272 29
0.0010 8.8335 30
0.0007 8.9168 31
0.0007 8.9992 32
0.0006 9.0661 33
0.0007 9.1103 34
0.0004 9.1424 35
0.0008 9.1573 36
0.0006 9.1666 37
0.0008 9.1732 38
0.0004 9.1781 39
0.0006 9.1867 40
0.0005 9.1986 41
0.0005 9.2203 42
0.0005 9.2512 43
0.0006 9.2889 44
0.0005 9.3360 45
0.0007 9.3759 46
0.0004 9.4144 47
0.0006 9.4461 48
0.0004 9.4718 49
0.0005 9.5113 50
0.0004 9.5425 51
0.0003 9.5667 52
0.0015 9.5468 53
0.0003 9.4515 54
0.0005 9.3881 55
0.0006 9.3797 56
0.0006 9.3887 57
0.0003 9.4038 58
0.0004 9.4206 59
0.0003 9.4417 60

Framework versions

  • Transformers 4.44.2
  • TensorFlow 2.17.0
  • Datasets 3.0.1
  • Tokenizers 0.19.1