readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-german-cased-finetuned-200labels
    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. -->
  
  # bert-base-german-cased-finetuned-200labels
  
  This model is a fine-tuned version of [ogimgio/bert-base-german-cased-finetuned-7labels](https://huggingface.co/ogimgio/bert-base-german-cased-finetuned-7labels) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0744
  - Micro f1: 0.0894
  - Macro f1: 0.0538
  
  ## 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: 3e-06
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: constant
  - num_epochs: 50
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Micro f1 | Macro f1 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
  | 0.8041        | 1.0   | 1380  | 0.7312          | 0.0422   | 0.0413   |
  | 0.605         | 2.0   | 2760  | 0.5440          | 0.0436   | 0.0423   |
  | 0.4455        | 3.0   | 4140  | 0.4026          | 0.0478   | 0.0449   |
  | 0.3317        | 4.0   | 5520  | 0.3070          | 0.0574   | 0.0516   |
  | 0.2553        | 5.0   | 6900  | 0.2432          | 0.0682   | 0.0599   |
  | 0.2041        | 6.0   | 8280  | 0.1982          | 0.0759   | 0.0657   |
  | 0.167         | 7.0   | 9660  | 0.1653          | 0.0798   | 0.0677   |
  | 0.1403        | 8.0   | 11040 | 0.1417          | 0.0839   | 0.0693   |
  | 0.1222        | 9.0   | 12420 | 0.1249          | 0.0865   | 0.0695   |
  | 0.109         | 10.0  | 13800 | 0.1132          | 0.0880   | 0.0684   |
  | 0.0999        | 11.0  | 15180 | 0.1052          | 0.0874   | 0.0661   |
  | 0.0941        | 12.0  | 16560 | 0.0994          | 0.0878   | 0.0655   |
  | 0.089         | 13.0  | 17940 | 0.0951          | 0.0876   | 0.0640   |
  | 0.0854        | 14.0  | 19320 | 0.0917          | 0.0888   | 0.0638   |
  | 0.0831        | 15.0  | 20700 | 0.0890          | 0.0889   | 0.0626   |
  | 0.0804        | 16.0  | 22080 | 0.0869          | 0.0890   | 0.0616   |
  | 0.0788        | 17.0  | 23460 | 0.0851          | 0.0890   | 0.0606   |
  | 0.077         | 18.0  | 24840 | 0.0835          | 0.0894   | 0.0599   |
  | 0.0759        | 19.0  | 26220 | 0.0822          | 0.0894   | 0.0593   |
  | 0.0745        | 20.0  | 27600 | 0.0811          | 0.0896   | 0.0588   |
  | 0.0735        | 21.0  | 28980 | 0.0800          | 0.0890   | 0.0573   |
  | 0.0728        | 22.0  | 30360 | 0.0791          | 0.0888   | 0.0564   |
  | 0.0716        | 23.0  | 31740 | 0.0783          | 0.0895   | 0.0559   |
  | 0.0709        | 24.0  | 33120 | 0.0775          | 0.0900   | 0.0556   |
  | 0.0698        | 25.0  | 34500 | 0.0768          | 0.0896   | 0.0550   |
  | 0.0694        | 26.0  | 35880 | 0.0761          | 0.0897   | 0.0548   |
  | 0.069         | 27.0  | 37260 | 0.0755          | 0.0892   | 0.0545   |
  | 0.0684        | 28.0  | 38640 | 0.0750          | 0.0893   | 0.0541   |
  | 0.0679        | 29.0  | 40020 | 0.0744          | 0.0894   | 0.0538   |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  