Training in progress epoch 0
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            This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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:  
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            - Validation Loss:  
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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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps':  
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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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            ### Framework versions
         
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            This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 5.9286
         
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            - Validation Loss: 5.9157
         
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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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 8, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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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            | 5.9286     | 5.9157          | 0     |
         
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            ### Framework versions
         
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            version https://git-lfs.github.com/spec/v1
         
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            version https://git-lfs.github.com/spec/v1
         
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