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fintuned-bert-disfluency – AI Model by kapilchauhan | AlphaNeural AI
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kapilchauhan
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fintuned-bert-disfluency
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transformers
tf
bert
text-classification
generated_from_keras_callback
disfl_qa
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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fintuned-bert-disfluency
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: 0.0814
Train Sparse Categorical Accuracy: 0.9795
Validation Loss: 0.0816
Validation Sparse Categorical Accuracy: 0.9795
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', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Train Sparse Categorical Accuracy
Validation Loss
Validation Sparse Categorical Accuracy
Epoch
0.1105
0.9694
0.0821
0.9800
0
0.0942
0.9759
0.0987
0.9765
1
0.0814
0.9795
0.0816
0.9795
2
Framework versions
Transformers 4.21.3
TensorFlow 2.8.2
Datasets 2.4.0
Tokenizers 0.12.1
