readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  widget:
  - text: "12064SAN101WAZW05"
  - text: "11004SAN001AH01SM83"
  - text: "11004SAN002DE02SM46"
  - text: "11040HZG501WW01MT01"
  - text: "Stör. Tauchpumpen fest"
  model-index:
  - name: Klassifizierung-Sanitaer
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # Klassifizierung-Sanitaer
  
  This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4922
  - F1: 0.7374
  
  ## 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:
  - learning_rate: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.4874        | 1.0   | 11   | 1.0656          | 0.6124 |
  | 0.9892        | 2.0   | 22   | 0.6269          | 0.7374 |
  | 0.5846        | 3.0   | 33   | 0.4922          | 0.7374 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  