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Upload TFBertForTokenClassification

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  1. README.md +6 -6
  2. tf_model.h5 +2 -2
README.md CHANGED
@@ -14,8 +14,8 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.3167
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- - Validation Loss: 0.4221
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  - Epoch: 2
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  ## Model description
@@ -35,16 +35,16 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-06, 'decay_steps': 744, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
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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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- | 0.7900 | 0.5758 | 0 |
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- | 0.3790 | 0.4553 | 1 |
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- | 0.3167 | 0.4221 | 2 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.0505
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+ - Validation Loss: 0.1625
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  - Epoch: 2
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  ## Model description
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 744, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.1}
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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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+ | 0.2389 | 0.1769 | 0 |
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+ | 0.0682 | 0.1638 | 1 |
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+ | 0.0505 | 0.1625 | 2 |
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  ### Framework versions
tf_model.h5 CHANGED
@@ -1,3 +1,3 @@
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