bert-ner-test-1 – AI Model by chosenone80 | AlphaNeural AI

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chosenone80/
bert-ner-test-1

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token-classification

generated_from_keras_callback

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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chosenone80/bert-ner-test-1

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: 0.1319
Validation Loss: 0.0479
Train Precision: 0.9163
Train Recall: 0.9298
Train F1: 0.9230
Train Accuracy: 0.9874
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: {'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': 2e-05, 'decay_steps': 877, '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: float32

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.1319	0.0479	0.9163	0.9298	0.9230	0.9874	0

Framework versions

Transformers 4.35.2
TensorFlow 2.15.0
Datasets 2.17.1
Tokenizers 0.15.2