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DBERT_ZS_CleanCollision_v1.2 – AI Model by ratish | AlphaNeural AI
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ratish
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DBERT_ZS_CleanCollision_v1.2
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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/DBERT_ZS_CleanCollision_v1.2
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: 0.6513
Validation Loss: 0.9577
Train Accuracy: 0.5517
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': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 9960, '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
1.0615
1.0729
0.3448
0
0.9837
1.0893
0.3448
1
0.8903
0.9640
0.4483
2
0.7841
0.8889
0.5862
3
0.6513
0.9577
0.5517
4
Framework versions
Transformers 4.28.1
TensorFlow 2.12.0
Datasets 2.11.0
Tokenizers 0.13.3
