finetuned-distilbert-tim-alarms-clusters-ord

• 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

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• 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

Framework versions

• Transformers 4.38.2
• TensorFlow 2.15.0
• Tokenizers 0.15.2