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Paper-clustered – AI Model by Deep98 | AlphaNeural AI
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Deep98
/
Paper-clustered
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transformers
tf
distilbert
question-answering
generated_from_keras_callback
mit
endpoints_compatible
us
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Deep98/Paper-clustered
This model is a fine-tuned version of
nandysoham16/16-clustered_aug
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.4183
Train End Logits Accuracy: 0.8611
Train Start Logits Accuracy: 0.8785
Validation Loss: 0.2040
Validation End Logits Accuracy: 1.0
Validation Start Logits Accuracy: 1.0
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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 18, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Train End Logits Accuracy
Train Start Logits Accuracy
Validation Loss
Validation End Logits Accuracy
Validation Start Logits Accuracy
Epoch
0.4183
0.8611
0.8785
0.2040
1.0
1.0
0
Framework versions
Transformers 4.26.0
TensorFlow 2.9.2
Datasets 2.9.0
Tokenizers 0.13.2
