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QA-BERT – AI Model by paumena | AlphaNeural AI
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paumena
/
QA-BERT
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transformers
tf
bert
question-answering
generated_from_keras_callback
squad
apache-2.0
endpoints_compatible
us
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paumena/QA-BERT
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: 0.3103
Epoch: 4
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Evaluation metrics
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 27725, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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: mixed_float16
Training results
Train Loss
Epoch
1.2706
0
0.7859
1
0.5571
2
0.4067
3
0.3103
4
Framework versions
Transformers 4.30.1
TensorFlow 2.12.0
Datasets 2.12.0
Tokenizers 0.13.3
