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bert-finetuned-mrpc – AI Model by stefaniftime | AlphaNeural AI
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stefaniftime
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bert-finetuned-mrpc
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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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stefaniftime/bert-finetuned-mrpc
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: 0.6832
Train Accuracy: 0.6325
Validation Loss: 0.6260
Validation Accuracy: 0.6838
Epoch: 0
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': 0.001, '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
0.6832
0.6325
0.6260
0.6838
0
Framework versions
Transformers 4.32.1
TensorFlow 2.12.0
Datasets 2.14.4
Tokenizers 0.13.3
