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bert-finetuned-ner_tf – AI Model by Surbhipatil | AlphaNeural AI
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Surbhipatil
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bert-finetuned-ner_tf
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transformers
tf
bert
token-classification
generated_from_keras_callback
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Surbhipatil/bert-finetuned-ner_tf
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: 0.0275
Validation Loss: 0.0515
Epoch: 2
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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2634, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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: mixed_float16
Training results
Train Loss
Validation Loss
Epoch
0.1725
0.0614
0
0.0481
0.0535
1
0.0275
0.0515
2
Framework versions
Transformers 4.48.3
TensorFlow 2.18.0
Datasets 3.3.2
Tokenizers 0.21.0
