finetuned-distilbert-tim-alarms-clusters-ord

This model is a fine-tuned version of giogenna16/pretrained-distilbert-tim-alarms-clusters-ord on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.1970
• Train Categorical Accuracy: 0.9058
• Train Categorical True Positives: 6890.0
• Train Categorical False Negatives: 588.0
• Train Categorical False Positives: 573.0
• Train Categorical True Negatives: 4269.0
• 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': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Categorical Accuracy	Train Categorical True Positives	Train Categorical False Negatives	Train Categorical False Positives	Train Categorical True Negatives	Epoch
0.5356	0.7289	6327.0	1151.0	2189.0	2653.0	0
0.2885	0.8661	6664.0	814.0	836.0	4006.0	1
0.1970	0.9058	6890.0	588.0	573.0	4269.0	2

Framework versions

• Transformers 4.38.2
• TensorFlow 2.15.0
• Tokenizers 0.15.2