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Training in progress epoch 0

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  1. README.md +5 -5
  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 [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-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: 0.8975
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- - Validation Loss: 0.8652
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- - Train Accuracy: 1.0
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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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 50, '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 Accuracy | Epoch |
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  |:----------:|:---------------:|:--------------:|:-----:|
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- | 0.8975 | 0.8652 | 1.0 | 0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-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: 1.2434
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+ - Validation Loss: 1.0000
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+ - Train Accuracy: 0.7222
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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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 200, '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 Accuracy | Epoch |
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  |:----------:|:---------------:|:--------------:|:-----:|
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+ | 1.2434 | 1.0000 | 0.7222 | 0 |
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  ### Framework versions
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