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Training in progress epoch 0

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  1. README.md +6 -6
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,10 +14,10 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.2589
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- - Train Accuracy: 0.9140
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- - Validation Loss: 0.1115
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- - Validation Accuracy: 0.9791
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  - Epoch: 0
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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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 108, '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-07, 'amsgrad': False}
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  - training_precision: float32
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  ### Training results
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  | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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  |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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- | 0.2589 | 0.9140 | 0.1115 | 0.9791 | 0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.9094
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+ - Train Accuracy: 0.6446
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+ - Validation Loss: 0.4812
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+ - Validation Accuracy: 0.9512
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  - Epoch: 0
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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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 24, '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-07, 'amsgrad': False}
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  - training_precision: float32
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  ### Training results
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  | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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  |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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+ | 0.9094 | 0.6446 | 0.4812 | 0.9512 | 0 |
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  ### Framework versions
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