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osc-01-bert-finetuned – AI Model by felixshier | AlphaNeural AI
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felixshier
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osc-01-bert-finetuned
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transformers
tf
bert
text-classification
generated_from_keras_callback
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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osc-01-bert-finetuned
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: 0.3193
Validation Loss: 0.7572
Train Precision: 0.6026
Epoch: 6
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 110, '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
Epoch
0.6873
0.6937
0.5147
0
0.6544
0.6854
0.5
1
0.6127
0.7071
0.5242
2
0.5651
0.6813
0.5591
3
0.5015
0.7012
0.5747
4
0.4006
0.7292
0.5882
5
0.3193
0.7572
0.6026
6
Framework versions
Transformers 4.31.0
TensorFlow 2.13.0
Datasets 2.14.4
Tokenizers 0.13.3
