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bert-finetuned-ner-prompts – AI Model by asif2926 | AlphaNeural AI
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asif2926
/
bert-finetuned-ner-prompts
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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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asif2926/bert-finetuned-ner-prompts
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: 0.6174
Validation Loss: 1.6737
Epoch: 7
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': 2032, '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
1.5336
2.1663
0
1.1415
2.0900
1
0.9941
1.9702
2
0.8658
1.8114
3
0.7632
1.7046
4
0.6897
1.6326
5
0.6430
1.6559
6
0.6174
1.6737
7
Framework versions
Transformers 4.50.0
TensorFlow 2.18.0
Datasets 3.5.0
Tokenizers 0.21.1
