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