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drugobert_spec – AI Model by danielsz96 | AlphaNeural AI
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danielsz96
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drugobert_spec
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transformers
tf
bert
token-classification
generated_from_keras_callback
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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drugobert_spec
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.2531
Train Precision: 0.4705
Train Recall: 0.2187
Train F1: 0.2986
Train Accuracy: 0.9374
Epoch: 3
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': 177, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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: float32
Training results
Train Loss
Train Precision
Train Recall
Train F1
Train Accuracy
Epoch
0.5777
0.0
0.0
0.0
0.9210
0
0.3068
0.5824
0.1243
0.2049
0.9306
1
0.2659
0.4706
0.2191
0.2990
0.9374
2
0.2531
0.4705
0.2187
0.2986
0.9374
3
Framework versions
Transformers 4.35.2
TensorFlow 2.14.0
Datasets 2.16.1
Tokenizers 0.15.1
