bert-finetuned-ner

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Mhammad2023/bert-finetuned-ner

This model is a fine-tuned version of bert-base-cased on an the CoNLL-2003 dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0271
• Validation Loss: 0.0523
• 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

Framework versions

• Transformers 4.52.4
• TensorFlow 2.18.0
• Datasets 3.6.0
• Tokenizers 0.21.1