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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: sevvalkapcak/newModel2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# sevvalkapcak/newModel2 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0158 |
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- Validation Loss: 0.4239 |
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- Train Accuracy: 0.933 |
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- Epoch: 35 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:--------------:|:-----:| |
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| 0.2465 | 0.2029 | 0.9085 | 0 | |
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| 0.1354 | 0.1302 | 0.939 | 1 | |
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| 0.1121 | 0.1588 | 0.934 | 2 | |
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| 0.0945 | 0.1551 | 0.937 | 3 | |
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| 0.0815 | 0.1696 | 0.939 | 4 | |
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| 0.0778 | 0.1647 | 0.932 | 5 | |
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| 0.0522 | 0.2356 | 0.931 | 6 | |
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| 0.0444 | 0.2861 | 0.9335 | 7 | |
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| 0.0329 | 0.2144 | 0.9355 | 8 | |
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| 0.0290 | 0.2548 | 0.935 | 9 | |
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| 0.0222 | 0.2866 | 0.93 | 10 | |
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| 0.0256 | 0.2787 | 0.9385 | 11 | |
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| 0.0267 | 0.2764 | 0.941 | 12 | |
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| 0.0201 | 0.2888 | 0.9315 | 13 | |
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| 0.0221 | 0.2737 | 0.934 | 14 | |
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| 0.0174 | 0.4403 | 0.93 | 15 | |
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| 0.0170 | 0.2836 | 0.932 | 16 | |
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| 0.0214 | 0.3033 | 0.9375 | 17 | |
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| 0.0125 | 0.3894 | 0.934 | 18 | |
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| 0.0271 | 0.3687 | 0.9305 | 19 | |
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| 0.0154 | 0.3817 | 0.9305 | 20 | |
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| 0.0149 | 0.4736 | 0.93 | 21 | |
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| 0.0196 | 0.4435 | 0.9325 | 22 | |
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| 0.0124 | 0.4873 | 0.929 | 23 | |
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| 0.0157 | 0.4008 | 0.932 | 24 | |
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| 0.0153 | 0.4074 | 0.931 | 25 | |
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| 0.0176 | 0.3996 | 0.9295 | 26 | |
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| 0.0160 | 0.3652 | 0.9355 | 27 | |
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| 0.0081 | 0.4446 | 0.934 | 28 | |
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| 0.0098 | 0.5249 | 0.934 | 29 | |
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| 0.0151 | 0.4112 | 0.937 | 30 | |
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| 0.0124 | 0.4888 | 0.929 | 31 | |
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| 0.0146 | 0.5022 | 0.9325 | 32 | |
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| 0.0130 | 0.5585 | 0.9305 | 33 | |
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| 0.0102 | 0.4304 | 0.935 | 34 | |
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| 0.0158 | 0.4239 | 0.933 | 35 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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