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Labira
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LabiraPJOK_3_100_Full

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bert
generated_from_keras_callback
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LabiraPJOK_3_100_Full / README.md
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metadata
library_name: transformers
license: mit
base_model: Labira/LabiraPJOK_2_100_Full
tags:
  - generated_from_keras_callback
model-index:
  - name: Labira/LabiraPJOK_3_100_Full
    results: []

Labira/LabiraPJOK_3_100_Full

This model is a fine-tuned version of Labira/LabiraPJOK_2_100_Full on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.0020
  • Validation Loss: 0.0007
  • Epoch: 75

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': 1100, '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
2.7614 1.1522 0
1.5531 0.5524 1
1.0482 0.2232 2
0.5443 0.0847 3
0.5227 0.0529 4
0.2873 0.0412 5
0.2568 0.0330 6
0.1310 0.0190 7
0.1108 0.0067 8
0.1252 0.0117 9
0.0740 0.0071 10
0.0507 0.0059 11
0.0790 0.0058 12
0.0282 0.0036 13
0.0562 0.0070 14
0.0850 0.0047 15
0.0715 0.0176 16
0.0724 0.0077 17
0.0361 0.0024 18
0.0266 0.0029 19
0.0207 0.0026 20
0.0158 0.0023 21
0.0086 0.0016 22
0.0214 0.0093 23
0.0327 0.0063 24
0.0102 0.0016 25
0.0072 0.0012 26
0.0273 0.0024 27
0.0185 0.0034 28
0.0091 0.0018 29
0.0144 0.0021 30
0.0107 0.0032 31
0.0632 0.0037 32
0.0149 0.0034 33
0.0151 0.0103 34
0.0195 0.0081 35
0.0145 0.0023 36
0.0150 0.0012 37
0.0126 0.0018 38
0.0068 0.0017 39
0.0057 0.0014 40
0.0075 0.0015 41
0.0035 0.0015 42
0.0059 0.0013 43
0.0040 0.0010 44
0.0036 0.0009 45
0.0040 0.0011 46
0.0058 0.0020 47
0.0801 0.0013 48
0.0062 0.0014 49
0.0049 0.0011 50
0.0057 0.0012 51
0.0023 0.0011 52
0.0047 0.0007 53
0.0041 0.0006 54
0.0056 0.0012 55
0.0035 0.0016 56
0.0042 0.0011 57
0.0029 0.0006 58
0.0025 0.0004 59
0.0229 0.0085 60
0.0057 0.0075 61
0.0038 0.0050 62
0.0047 0.0014 63
0.0024 0.0006 64
0.0021 0.0005 65
0.0480 0.0008 66
0.0041 0.0010 67
0.0038 0.0010 68
0.0032 0.0010 69
0.0037 0.0009 70
0.0027 0.0007 71
0.0041 0.0007 72
0.0039 0.0006 73
0.0024 0.0007 74
0.0020 0.0007 75

Framework versions

  • Transformers 4.46.2
  • TensorFlow 2.17.0
  • Datasets 3.1.0
  • Tokenizers 0.20.3