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BioASQ-DistilBERT – AI Model by paumena | AlphaNeural AI
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paumena
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BioASQ-DistilBERT
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transformers
tf
distilbert
question-answering
generated_from_keras_callback
apache-2.0
endpoints_compatible
us
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paumena/BioASQ-DistilBERT
This model is a fine-tuned version of
paumena/QA-DistilBERT
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.4425
Epoch: 4
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
{'exact_match': 79.16666666666667, 'f1': 82.6398528671149}
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': 1225, '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
1.2076
0
0.6846
1
0.5395
2
0.4718
3
0.4425
4
Framework versions
Transformers 4.30.2
TensorFlow 2.12.0
Datasets 2.13.0
Tokenizers 0.13.3
