dok-ner-bert-base-multilingual-uncased – AI Model by mahabharahta | AlphaNeural AI

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mahabharahta/
dok-ner-bert-base-multilingual-uncased

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token-classification

generated_from_keras_callback

google-bert/bert-base-multilingual-uncased

autotrain_compatible

endpoints_compatible

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mahabharahta/dok-ner-bert-base-multilingual-uncased

This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.0008
Validation Loss: 0.0003
Train Precision: 1.0
Train Recall: 1.0
Train F1: 1.0
Train Accuracy: 1.0
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': 3279, '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: float32

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.0313	0.0006	1.0	1.0	1.0	1.0	0
0.0017	0.0004	1.0	1.0	1.0	1.0	1
0.0008	0.0003	1.0	1.0	1.0	1.0	2

Framework versions

Transformers 4.44.2
TensorFlow 2.17.0
Datasets 3.0.2
Tokenizers 0.19.1