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Training in progress epoch 0

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  1. README.md +5 -6
  2. tf_model.h5 +1 -1
  3. tokenizer.json +14 -2
README.md CHANGED
@@ -14,9 +14,9 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.5848
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- - Validation Loss: 0.3793
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- - Epoch: 1
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  ## Model description
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@@ -35,15 +35,14 @@ 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': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -964, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, '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: mixed_float16
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  ### Training results
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  | Train Loss | Validation Loss | Epoch |
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  |:----------:|:---------------:|:-----:|
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- | 0.8490 | 0.6901 | 0 |
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- | 0.5848 | 0.3793 | 1 |
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  ### Framework versions
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.1380
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+ - Validation Loss: 0.1630
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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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -861, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, '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: mixed_float16
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  ### Training results
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  | Train Loss | Validation Loss | Epoch |
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  |:----------:|:---------------:|:-----:|
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+ | 0.1380 | 0.1630 | 0 |
 
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  ### Framework versions
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