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albert-base-v2-finetuned-mnli – AI Model by svenbl80 | AlphaNeural AI
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svenbl80
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albert-base-v2-finetuned-mnli
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transformers
tf
tensorboard
albert
text-classification
generated_from_keras_callback
apache-2.0
autotrain_compatible
endpoints_compatible
us
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svenbl80/albert-base-v2-finetuned-mnli
This model is a fine-tuned version of
albert-base-v2
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.2712
Validation Loss: 0.4705
Train Accuracy: 0.8264
Epoch: 3
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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 736290, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, '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
0.5312
0.4792
0.8117
0
0.4204
0.4335
0.8344
1
0.3465
0.4351
0.8317
2
0.2712
0.4705
0.8264
3
Framework versions
Transformers 4.28.0
TensorFlow 2.7.0
Datasets 2.3.2
Tokenizers 0.12.1
