Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
patient_falls_detector_bert_cased – AI Model by Blaise-MR | AlphaNeural AI
You can deploy this model and start earning money today!
Blaise-MR
/
patient_falls_detector_bert_cased
like
0
transformers
tf
bert
text-classification
generated_from_keras_callback
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
patient_falls_detector_bert_cased
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: 0.2085
Train Accuracy: 0.9332
Validation Loss: 0.1532
Validation Accuracy: 0.9474
Epoch: 1
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': 5e-05, 'decay_steps': 1490, '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-07, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Train Accuracy
Validation Loss
Validation Accuracy
Epoch
0.3932
0.8291
0.1793
0.9624
0
0.2085
0.9332
0.1532
0.9474
1
Framework versions
Transformers 4.41.2
TensorFlow 2.15.0
Datasets 2.19.2
Tokenizers 0.19.1
