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my_distilbert_ft_model – AI Model by yinani24 | AlphaNeural AI
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yinani24
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my_distilbert_ft_model
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transformers
tf
distilbert
multiple-choice
generated_from_keras_callback
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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yinani24/my_distilbert_ft_model
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: 1.0997
Validation Loss: 1.0984
Train Accuracy: 0.1875
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: {'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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-06, 'decay_steps': 20, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Validation Loss
Train Accuracy
Epoch
1.0947
1.0989
0.25
0
1.0997
1.0984
0.1875
1
Framework versions
Transformers 4.35.0
TensorFlow 2.14.0
Datasets 2.14.6
Tokenizers 0.14.1
