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  ---
 
 
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  license: mit
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- tags:
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- - generated_from_keras_callback
 
 
 
 
 
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  model-index:
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- - name: Ruth/gbert-large-germaner
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- <!-- This model card has been generated automatically according to the information Keras had access to. You should
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- probably proofread and complete it, then remove this comment. -->
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- # Ruth/gbert-large-germaner
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- This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.0123
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- - Validation Loss: 0.0985
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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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 13915, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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: float32
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-
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- ### Training results
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-
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- | Train Loss | Validation Loss | Epoch |
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- |:----------:|:---------------:|:-----:|
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- | 0.1236 | 0.0807 | 0 |
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- | 0.0650 | 0.0781 | 1 |
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- | 0.0420 | 0.0770 | 2 |
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- | 0.0232 | 0.0843 | 3 |
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- | 0.0123 | 0.0985 | 4 |
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-
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  ### Framework versions
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  - Transformers 4.18.0
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- - TensorFlow 2.6.2
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  - Datasets 1.18.0
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  - Tokenizers 0.12.1
 
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  ---
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+ language:
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+ - de
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  license: mit
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+ datasets:
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+ - germaner
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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  model-index:
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+ - name: gbert-large-germaner
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: germaner
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+ type: germaner
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+ args: default
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+ metrics:
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+ - name: precision
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+ type: precision
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+ value: 0.8693333333333333
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+ - name: recall
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+ type: recall
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+ value: 0.885640362225097
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+ - name: f1
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+ type: f1
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+ value: 0.8774110861903236
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+ - name: accuracy
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+ type: accuracy
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+ value: 0.9784210744831022
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+ # gbert-large-germaner
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+ This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on the germaner dataset.
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  It achieves the following results on the evaluation set:
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+ - precision: 0.8693
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+ - recall: 0.8856
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+ - f1: 0.8774
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+ - accuracy: 0.9784
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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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+ - num_train_epochs: 5
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - learning_rate: 2e-05
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+ - weight_decay_rate: 0.01
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+ - num_warmup_steps: 0
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+ - fp16: True
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.18.0
 
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  - Datasets 1.18.0
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  - Tokenizers 0.12.1