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destillbert-uncased-future_statements – AI Model by jonaskoenig | AlphaNeural AI
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destillbert-uncased-future_statements
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transformers
tf
distilbert
text-classification
generated_from_keras_callback
apache-2.0
autotrain_compatible
endpoints_compatible
us
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jonaskoenig/destillbert-uncased-future_statements
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: 0.0092
Train Sparse Categorical Accuracy: 0.9975
Validation Loss: 0.0184
Validation Sparse Categorical Accuracy: 0.9954
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
0.0596
0.9804
0.0181
0.9953
0
0.0154
0.9957
0.0147
0.9959
1
0.0092
0.9975
0.0184
0.9954
2
Framework versions
Transformers 4.20.1
TensorFlow 2.9.1
Datasets 2.3.2
Tokenizers 0.12.1
