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Upload TFBertForSequenceClassification

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  1. README.md +9 -9
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -15,9 +15,9 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-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: 0.0839
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- - Validation Loss: 0.7750
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- - Train F1: 0.7755
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  - Epoch: 4
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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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1990, '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 | Train F1 | Epoch |
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  |:----------:|:---------------:|:--------:|:-----:|
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- | 0.5526 | 0.6443 | 0.7416 | 0 |
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- | 0.3883 | 0.5055 | 0.7648 | 1 |
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- | 0.2366 | 0.5839 | 0.7772 | 2 |
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- | 0.1339 | 0.6715 | 0.7726 | 3 |
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- | 0.0839 | 0.7750 | 0.7755 | 4 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-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: 0.0955
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+ - Validation Loss: 0.5721
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+ - Train F1: 0.8418
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  - Epoch: 4
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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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 4790, '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 | Train F1 | Epoch |
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  |:----------:|:---------------:|:--------:|:-----:|
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+ | 0.5128 | 0.3961 | 0.8342 | 0 |
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+ | 0.3615 | 0.3747 | 0.8513 | 1 |
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+ | 0.2357 | 0.5269 | 0.8243 | 2 |
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+ | 0.1609 | 0.4436 | 0.8184 | 3 |
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+ | 0.0955 | 0.5721 | 0.8418 | 4 |
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  ### Framework versions
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