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bert-finetuned-ner – AI Model by JimmyWu | AlphaNeural AI
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JimmyWu
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bert-finetuned-ner
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transformers
tf
bert
token-classification
generated_from_keras_callback
apache-2.0
autotrain_compatible
endpoints_compatible
us
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JimmyWu/bert-finetuned-ner
This model is a fine-tuned version of
bert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.0086
Validation Loss: 0.0791
Epoch: 4
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: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1695, '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}
training_precision: float32
Training results
Train Loss
Validation Loss
Epoch
0.1328
0.0620
0
0.0391
0.0590
1
0.0211
0.0628
2
0.0120
0.0752
3
0.0086
0.0791
4
Framework versions
Transformers 4.18.0
TensorFlow 2.8.0
Datasets 2.1.0
Tokenizers 0.12.1
