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MariaDB10Classic_Unbalance
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0400
- Train Accuracy: 0.9858
- Validation Loss: 0.3020
- Validation Accuracy: 0.9472
- Epoch: 6
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': 0.001, 'clipnorm': 1.0, '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': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
---|---|---|---|---|
0.3219 | 0.8971 | 0.1939 | 0.9523 | 0 |
0.2500 | 0.9163 | 0.2026 | 0.9523 | 1 |
0.2343 | 0.9155 | 0.1975 | 0.9523 | 2 |
0.1885 | 0.9331 | 0.1921 | 0.9523 | 3 |
0.1486 | 0.9381 | 0.2421 | 0.9523 | 4 |
0.1038 | 0.9506 | 0.2599 | 0.9372 | 5 |
0.0400 | 0.9858 | 0.3020 | 0.9472 | 6 |
Framework versions
- Transformers 4.29.2
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3