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

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# finetuned-distilbert-tim-alarms-clusters-ord

This model is a fine-tuned version of [giogenna16/pretrained-distilbert-tim-alarms-clusters-ord](https://huggingface.co/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