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MariaDB20ALBERT_Unbalance
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: 0.0754
- Train Accuracy: 0.9808
- Validation Loss: 0.1763
- Validation Accuracy: 0.9548
- Epoch: 7
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 |
|---|---|---|---|---|
| 0.2348 | 0.9356 | 0.1533 | 0.9698 | 0 |
| 0.2017 | 0.9364 | 0.1380 | 0.9698 | 1 |
| 0.1968 | 0.9372 | 0.1435 | 0.9698 | 2 |
| 0.1729 | 0.9372 | 0.1365 | 0.9673 | 3 |
| 0.1448 | 0.9490 | 0.1350 | 0.9673 | 4 |
| 0.1314 | 0.9523 | 0.1401 | 0.9648 | 5 |
| 0.1095 | 0.9690 | 0.1530 | 0.9673 | 6 |
| 0.0754 | 0.9808 | 0.1763 | 0.9548 | 7 |
Framework versions
- Transformers 4.29.2
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
