metadata
base_model: giogenna16/pretrained-distilbert-tim-alarms-clusters-ord
tags:
- generated_from_keras_callback
model-index:
- name: finetuned-distilbert-tim-alarms-clusters-ord
results: []
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