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Thamer/electra-fine-tuned
This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.6869
- Train Binary Accuracy: 0.5541
- Validation Loss: 0.7140
- Validation Binary Accuracy: 0.5092
- Train F1: 0.6748
- Epoch: 2
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0002, 'decay_steps': 3156, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Binary Accuracy | Validation Loss | Validation Binary Accuracy | Train F1 | Epoch |
|---|---|---|---|---|---|
| 0.7292 | 0.6233 | 0.7062 | 0.5092 | 0.6748 | 0 |
| 0.6881 | 0.5551 | 0.7137 | 0.5092 | 0.6748 | 1 |
| 0.6869 | 0.5541 | 0.7140 | 0.5092 | 0.6748 | 2 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.11.0
- Datasets 2.13.1
- Tokenizers 0.13.3
