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--- |
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library_name: transformers |
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license: mit |
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base_model: Labira/LabiraPJOK_1_50 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Labira/LabiraPJOK_2x_50 |
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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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# Labira/LabiraPJOK_2x_50 |
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This model is a fine-tuned version of [Labira/LabiraPJOK_1_50](https://huggingface.co/Labira/LabiraPJOK_1_50) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0131 |
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- Validation Loss: 4.2318 |
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- Epoch: 44 |
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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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 250, '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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 4.4264 | 3.9800 | 0 | |
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| 3.0757 | 3.5083 | 1 | |
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| 2.2362 | 3.1869 | 2 | |
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| 1.5246 | 2.7953 | 3 | |
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| 0.9065 | 2.8214 | 4 | |
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| 0.7330 | 3.3041 | 5 | |
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| 0.6050 | 3.4187 | 6 | |
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| 0.5238 | 3.4963 | 7 | |
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| 0.3471 | 3.4544 | 8 | |
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| 0.2836 | 3.1970 | 9 | |
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| 0.4074 | 3.1324 | 10 | |
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| 0.1832 | 3.2997 | 11 | |
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| 0.1899 | 3.5169 | 12 | |
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| 0.0939 | 3.5228 | 13 | |
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| 0.1638 | 3.3909 | 14 | |
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| 0.1055 | 3.4798 | 15 | |
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| 0.0827 | 3.6602 | 16 | |
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| 0.1070 | 3.7096 | 17 | |
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| 0.0751 | 3.7451 | 18 | |
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| 0.0449 | 3.7821 | 19 | |
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| 0.0299 | 3.8203 | 20 | |
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| 0.0505 | 3.8744 | 21 | |
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| 0.0247 | 3.9163 | 22 | |
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| 0.0534 | 3.9760 | 23 | |
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| 0.0442 | 4.0388 | 24 | |
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| 0.0211 | 4.0753 | 25 | |
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| 0.0216 | 4.0966 | 26 | |
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| 0.0219 | 4.1131 | 27 | |
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| 0.0234 | 4.1117 | 28 | |
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| 0.0255 | 4.1391 | 29 | |
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| 0.0199 | 4.1682 | 30 | |
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| 0.0196 | 4.1973 | 31 | |
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| 0.0317 | 4.2302 | 32 | |
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| 0.0263 | 4.2538 | 33 | |
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| 0.0322 | 4.2648 | 34 | |
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| 0.0171 | 4.2541 | 35 | |
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| 0.0200 | 4.2429 | 36 | |
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| 0.0201 | 4.2240 | 37 | |
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| 0.0331 | 4.1675 | 38 | |
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| 0.0220 | 4.1519 | 39 | |
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| 0.0158 | 4.1661 | 40 | |
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| 0.0131 | 4.1824 | 41 | |
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| 0.0174 | 4.2002 | 42 | |
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| 0.0170 | 4.2208 | 43 | |
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| 0.0131 | 4.2318 | 44 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- TensorFlow 2.17.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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