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bert-finetuned-ner – AI Model by SnehilDey | AlphaNeural AI
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SnehilDey
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bert-finetuned-ner
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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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SnehilDey/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: 0.0684
Validation Loss: 0.0585
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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 1109, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Epoch
0.0686
0.0585
0
0.0694
0.0585
1
0.0684
0.0585
2
Framework versions
Transformers 4.45.1
TensorFlow 2.16.1
Datasets 3.0.1
Tokenizers 0.20.0
