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bert-finetuned-ASAP-AEStask – AI Model by raoel | AlphaNeural AI
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raoel
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bert-finetuned-ASAP-AEStask
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transformers
tf
bert
text-classification
generated_from_keras_callback
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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raoel/bert-finetuned-ASAP-AEStask
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: 0.3250
Epoch: 4
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': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Epoch
1.1863
0
0.8763
1
0.7140
2
0.5078
3
0.3250
4
Framework versions
Transformers 4.33.0
TensorFlow 2.12.0
Datasets 2.1.0
Tokenizers 0.13.3
