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distillbert_qas – AI Model by Varun-George03 | AlphaNeural AI
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Varun-George03
/
distillbert_qas
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transformers
tf
distilbert
question-answering
generated_from_keras_callback
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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Varun-George03/distillbert_qas
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.9050
Epoch: 1
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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 16422, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
training_precision: mixed_float16
Training results
Train Loss
Epoch
1.2584
0
0.9050
1
Framework versions
Transformers 4.34.1
TensorFlow 2.14.0
Datasets 2.14.6
Tokenizers 0.14.1
