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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_3x_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_5x_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_5x_50 |
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This model is a fine-tuned version of [Labira/LabiraPJOK_3x_50](https://huggingface.co/Labira/LabiraPJOK_3x_50) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0274 |
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- Validation Loss: 3.1328 |
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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': 150, '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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| 3.2696 | 2.9298 | 0 | |
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| 1.9565 | 2.6626 | 1 | |
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| 1.6690 | 2.7837 | 2 | |
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| 1.1679 | 2.9196 | 3 | |
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| 1.0975 | 2.8046 | 4 | |
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| 0.8930 | 2.6822 | 5 | |
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| 0.6527 | 2.6118 | 6 | |
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| 0.5637 | 2.5444 | 7 | |
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| 0.4854 | 2.5175 | 8 | |
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| 0.4389 | 2.5464 | 9 | |
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| 0.3206 | 2.5893 | 10 | |
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| 0.3225 | 2.6538 | 11 | |
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| 0.1880 | 2.7504 | 12 | |
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| 0.1288 | 2.8371 | 13 | |
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| 0.1381 | 2.9128 | 14 | |
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| 0.0994 | 2.9468 | 15 | |
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| 0.1544 | 2.9312 | 16 | |
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| 0.0978 | 2.9279 | 17 | |
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| 0.0492 | 2.9426 | 18 | |
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| 0.0612 | 2.9733 | 19 | |
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| 0.1016 | 3.0228 | 20 | |
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| 0.0554 | 3.0772 | 21 | |
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| 0.0768 | 3.1331 | 22 | |
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| 0.0277 | 3.1720 | 23 | |
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| 0.0403 | 3.1906 | 24 | |
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| 0.0730 | 3.1962 | 25 | |
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| 0.0204 | 3.1958 | 26 | |
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| 0.0731 | 3.1981 | 27 | |
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| 0.0414 | 3.1874 | 28 | |
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| 0.0316 | 3.1657 | 29 | |
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| 0.0324 | 3.1507 | 30 | |
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| 0.0526 | 3.1275 | 31 | |
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| 0.0369 | 3.1141 | 32 | |
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| 0.0406 | 3.1091 | 33 | |
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| 0.0214 | 3.1127 | 34 | |
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| 0.0209 | 3.1207 | 35 | |
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| 0.0139 | 3.1172 | 36 | |
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| 0.0215 | 3.1166 | 37 | |
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| 0.0140 | 3.1168 | 38 | |
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| 0.0277 | 3.1187 | 39 | |
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| 0.0131 | 3.1214 | 40 | |
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| 0.0184 | 3.1226 | 41 | |
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| 0.0286 | 3.1256 | 42 | |
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| 0.0144 | 3.1297 | 43 | |
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| 0.0274 | 3.1328 | 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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