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classiv1_albert_model – AI Model by saada2024 | AlphaNeural AI
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saada2024
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classiv1_albert_model
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transformers
tf
albert
text-classification
generated_from_keras_callback
albert/albert-base-v2
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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classiv1_albert_model
This model is a fine-tuned version of
albert/albert-base-v2
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.1577
Train Accuracy: 0.9334
Validation Loss: 0.2818
Validation Accuracy: 0.8990
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', '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': np.float32(3e-05), 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Train Accuracy
Validation Loss
Validation Accuracy
Epoch
0.9344
0.6647
0.4468
0.8440
0
0.2788
0.9076
0.2503
0.9170
1
0.1689
0.9293
0.2698
0.9110
2
0.1577
0.9334
0.2818
0.8990
3
Framework versions
Transformers 4.52.4
TensorFlow 2.19.0
Datasets 3.6.0
Tokenizers 0.21.1
