newModel2 / README.md
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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: 0.0178
  • Validation Loss: 0.4578
  • Train Accuracy: 0.9285
  • Epoch: 39

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

Framework versions

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