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sevvalkapcak
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newModel2

Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
Inference Endpoints
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newModel2 / README.md
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sevvalkapcak
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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: sevvalkapcak/newModel2
    results: []

sevvalkapcak/newModel2

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

  • Train Loss: 0.0177
  • Validation Loss: 0.5256
  • Train Accuracy: 0.923
  • Epoch: 73

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': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Epoch
0.2465 0.2029 0.9085 0
0.1354 0.1302 0.939 1
0.1121 0.1588 0.934 2
0.0945 0.1551 0.937 3
0.0815 0.1696 0.939 4
0.0778 0.1647 0.932 5
0.0522 0.2356 0.931 6
0.0444 0.2861 0.9335 7
0.0329 0.2144 0.9355 8
0.0290 0.2548 0.935 9
0.0222 0.2866 0.93 10
0.0256 0.2787 0.9385 11
0.0267 0.2764 0.941 12
0.0201 0.2888 0.9315 13
0.0221 0.2737 0.934 14
0.0174 0.4403 0.93 15
0.0170 0.2836 0.932 16
0.0214 0.3033 0.9375 17
0.0125 0.3894 0.934 18
0.0271 0.3687 0.9305 19
0.0154 0.3817 0.9305 20
0.0149 0.4736 0.93 21
0.0196 0.4435 0.9325 22
0.0124 0.4873 0.929 23
0.0157 0.4008 0.932 24
0.0153 0.4074 0.931 25
0.0176 0.3996 0.9295 26
0.0160 0.3652 0.9355 27
0.0081 0.4446 0.934 28
0.0098 0.5249 0.934 29
0.0151 0.4112 0.937 30
0.0124 0.4888 0.929 31
0.0146 0.5022 0.9325 32
0.0130 0.5585 0.9305 33
0.0102 0.4304 0.935 34
0.0158 0.4239 0.933 35
0.0156 0.4849 0.93 36
0.0153 0.5097 0.9245 37
0.0135 0.4689 0.934 38
0.0178 0.4578 0.9285 39
0.0124 0.4083 0.9275 40
0.0106 0.4946 0.926 41
0.0098 0.4908 0.927 42
0.0131 0.5604 0.928 43
0.0143 0.4226 0.9315 44
0.0105 0.5664 0.9245 45
0.0189 0.5121 0.925 46
0.0148 0.5259 0.9245 47
0.0090 0.4567 0.9295 48
0.0156 0.4633 0.926 49
0.0128 0.5222 0.9295 50
0.0118 0.5461 0.921 51
0.0172 0.4626 0.927 52
0.0129 0.5266 0.922 53
0.0159 0.5203 0.925 54
0.0106 0.5360 0.9265 55
0.0158 0.4766 0.9305 56
0.0106 0.5630 0.926 57
0.0142 0.6162 0.922 58
0.0137 0.5518 0.916 59
0.0083 0.6281 0.9155 60
0.0071 0.6263 0.9245 61
0.0116 0.6166 0.9235 62
0.0162 0.5217 0.9195 63
0.0158 0.6366 0.9215 64
0.0120 0.5511 0.9245 65
0.0093 0.4895 0.9225 66
0.0094 0.5207 0.9255 67
0.0067 0.6252 0.9275 68
0.0058 0.6934 0.9235 69
0.0055 0.6577 0.928 70
0.0073 0.5865 0.9255 71
0.0336 0.4875 0.9175 72
0.0177 0.5256 0.923 73

Framework versions

  • Transformers 4.35.2
  • TensorFlow 2.15.0
  • Datasets 2.16.1
  • Tokenizers 0.15.1