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bert-finetuned-ner – AI Model by unfixbug | AlphaNeural AI
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unfixbug
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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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unfixbug/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: 0.0272
Validation Loss: 0.0560
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': np.float32(0.9), 'beta_2': np.float32(0.999), 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32
Training results
Train Loss
Validation Loss
Epoch
0.1761
0.0650
0
0.0480
0.0576
1
0.0272
0.0560
2
Framework versions
Transformers 4.51.3
TensorFlow 2.18.0
Datasets 3.5.1
Tokenizers 0.21.1
