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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/newModel |
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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/newModel |
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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: 0.0146 |
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- Validation Loss: 0.7180 |
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- Train Accuracy: 0.909 |
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- Epoch: 37 |
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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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| 0.0133 | 0.6573 | 0.901 | 0 | |
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| 0.0135 | 0.7314 | 0.9065 | 1 | |
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| 0.0104 | 0.6544 | 0.913 | 2 | |
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| 0.0148 | 0.7763 | 0.9035 | 3 | |
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| 0.0171 | 0.7110 | 0.9055 | 4 | |
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| 0.0121 | 0.7075 | 0.9015 | 5 | |
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| 0.0126 | 0.7461 | 0.8945 | 6 | |
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| 0.0212 | 0.7539 | 0.9035 | 7 | |
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| 0.0183 | 0.7842 | 0.9005 | 8 | |
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| 0.0192 | 0.7431 | 0.901 | 9 | |
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| 0.0224 | 0.6014 | 0.9065 | 10 | |
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| 0.0168 | 0.6000 | 0.914 | 11 | |
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| 0.0133 | 0.6241 | 0.9125 | 12 | |
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| 0.0097 | 0.6747 | 0.9075 | 13 | |
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| 0.0122 | 0.7352 | 0.908 | 14 | |
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| 0.0123 | 0.8061 | 0.905 | 15 | |
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| 0.0139 | 0.7254 | 0.8985 | 16 | |
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| 0.0120 | 0.6856 | 0.903 | 17 | |
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| 0.0175 | 0.6727 | 0.905 | 18 | |
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| 0.0155 | 0.6912 | 0.9055 | 19 | |
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| 0.0192 | 0.7535 | 0.903 | 20 | |
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| 0.0206 | 0.7428 | 0.8995 | 21 | |
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| 0.0108 | 0.7883 | 0.8965 | 22 | |
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| 0.0159 | 0.7443 | 0.8885 | 23 | |
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| 0.0238 | 0.7381 | 0.8935 | 24 | |
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| 0.0167 | 0.7888 | 0.901 | 25 | |
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| 0.0207 | 0.7062 | 0.899 | 26 | |
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| 0.0148 | 0.7670 | 0.9065 | 27 | |
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| 0.0177 | 0.6694 | 0.8925 | 28 | |
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| 0.0157 | 0.7312 | 0.9045 | 29 | |
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| 0.0145 | 0.6551 | 0.905 | 30 | |
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| 0.0188 | 0.7582 | 0.906 | 31 | |
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| 0.0136 | 0.7531 | 0.9085 | 32 | |
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| 0.0119 | 0.7965 | 0.8905 | 33 | |
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| 0.0069 | 0.8430 | 0.901 | 34 | |
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| 0.0100 | 0.7795 | 0.8975 | 35 | |
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| 0.0100 | 0.9567 | 0.889 | 36 | |
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| 0.0146 | 0.7180 | 0.909 | 37 | |
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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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