<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. -->
ayshi/albert
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: 0.4479
- Validation Loss: 1.1225
- Train Accuracy: 0.7022
- Epoch: 9
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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 650, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 |
|---|---|---|---|
| 1.2151 | 1.1505 | 0.6667 | 0 |
| 1.1415 | 1.1152 | 0.6667 | 1 |
| 1.0302 | 1.1222 | 0.6667 | 2 |
| 0.8825 | 1.0611 | 0.68 | 3 |
| 0.7690 | 1.0625 | 0.6756 | 4 |
| 0.6847 | 1.0749 | 0.6711 | 5 |
| 0.5797 | 1.1264 | 0.6844 | 6 |
| 0.5174 | 1.1074 | 0.6978 | 7 |
| 0.4699 | 1.1323 | 0.6978 | 8 |
| 0.4479 | 1.1225 | 0.7022 | 9 |
Framework versions
- Transformers 4.34.0
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1
