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vTFqa-finetuned-distilbert-base-cased – AI Model by jmparejaz | AlphaNeural AI
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jmparejaz
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vTFqa-finetuned-distilbert-base-cased
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transformers
tf
distilbert
question-answering
generated_from_keras_callback
apache-2.0
endpoints_compatible
us
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jmparejaz/vTFqa-finetuned-distilbert-base-cased
This model is a fine-tuned version of
distilbert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 1.6312
Train End Logits Accuracy: 0.5702
Train Start Logits Accuracy: 0.5364
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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0002, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0002, 'decay_steps': 22180, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '
passive_serialization
': True}, 'warmup_steps': 2, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: float32
Training results
Train Loss
Train End Logits Accuracy
Train Start Logits Accuracy
Epoch
1.6312
0.5702
0.5364
0
Framework versions
Transformers 4.25.1
TensorFlow 2.9.2
Datasets 2.8.0
Tokenizers 0.13.2
