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bert-textClassification_v1.1 – AI Model by ratish | AlphaNeural AI
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ratish
/
bert-textClassification_v1.1
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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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ratish/bert-textClassification_v1.1
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: 1.2176
Validation Loss: 1.4740
Train Accuracy: 0.5909
Epoch: 4
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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 95, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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
2.2620
2.1136
0.3636
0
1.8161
1.8166
0.3864
1
1.4886
1.6061
0.5909
2
1.2862
1.5037
0.5909
3
1.2176
1.4740
0.5909
4
Framework versions
Transformers 4.27.4
TensorFlow 2.12.0
Datasets 2.11.0
Tokenizers 0.13.3
