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krissbert-sentence-classifier – AI Model by Meli101 | AlphaNeural AI
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Meli101
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krissbert-sentence-classifier
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transformers
tf
bert
text-classification
generated_from_keras_callback
microsoft/BiomedNLP-KRISSBERT-PubMed-UMLS-EL
finetune
mit
autotrain_compatible
endpoints_compatible
us
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Meli101/krissbert-sentence-classifier
This model is a fine-tuned version of
microsoft/BiomedNLP-KRISSBERT-PubMed-UMLS-EL
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.1489
Validation Loss: 0.2873
Train Precision: 0.9170
Train Recall: 0.9151
Train Accuracy: 0.9154
Train F1: 0.9151
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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1535, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Validation Loss
Train Precision
Train Recall
Train Accuracy
Train F1
Epoch
0.5011
0.3717
0.8777
0.8711
0.8723
0.8724
0
0.2382
0.3152
0.9012
0.8984
0.8991
0.8991
1
0.1489
0.2873
0.9170
0.9151
0.9154
0.9151
2
Framework versions
Transformers 4.35.2
TensorFlow 2.15.0
Datasets 2.17.1
Tokenizers 0.15.2
