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fine-tuned-bert_full – AI Model by Marivanna27 | AlphaNeural AI
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Marivanna27
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fine-tuned-bert_full
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transformers
tf
bert
text-classification
generated_from_keras_callback
google-bert/bert-base-multilingual-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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fine-tuned-bert_full
This model is a fine-tuned version of
google-bert/bert-base-multilingual-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.4738
Train Accuracy: 0.8120
Validation Loss: 0.7711
Validation Accuracy: 0.6894
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': 2e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Train Accuracy
Validation Loss
Validation Accuracy
Epoch
0.8973
0.5688
0.7976
0.6460
0
0.6204
0.7478
0.7341
0.7081
1
0.4738
0.8120
0.7711
0.6894
2
Framework versions
Transformers 4.48.2
TensorFlow 2.18.0
Tokenizers 0.21.0
