alenaa/evas_detection_tf

ev_detection

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0764
• Train Accuracy: 0.9727
• Validation Loss: 0.6513
• Validation Accuracy: 0.8366
• Epoch: 4

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': 1.0, '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': 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
0.6343	0.6245	0.4200	0.8218	0
0.3990	0.8501	0.4292	0.8317	1
0.2138	0.9207	0.4555	0.8218	2
0.1133	0.9641	0.5589	0.8267	3
0.0764	0.9727	0.6513	0.8366	4

Framework versions

• Transformers 4.28.1
• TensorFlow 2.12.0
• Tokenizers 0.13.3