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NER2.0.3-alpha_num_dataset – AI Model by sxandie | AlphaNeural AI
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sxandie
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NER2.0.3-alpha_num_dataset
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transformers
tf
tensorboard
bert
token-classification
generated_from_keras_callback
mit
autotrain_compatible
endpoints_compatible
us
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sxandie/NER2.0.3-alpha_num_dataset
This model is a fine-tuned version of
deepset/gbert-base
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.3026
Validation Loss: 0.2050
Epoch: 0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
optimizer: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 29135, '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}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Epoch
0.3026
0.2050
0
Framework versions
Transformers 4.30.2
TensorFlow 2.12.0
Datasets 2.2.2
Tokenizers 0.13.3
