readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-german-cased-finetuned-200labels-notrandom
    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-notrandom
  
  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: 0.1007
  - Micro f1: 0.1030
  - Macro f1: 0.0788
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
  | 0.8788        | 1.0   | 1380  | 0.8018          | 0.0855   | 0.0920   |
  | 0.6458        | 2.0   | 2760  | 0.5829          | 0.0884   | 0.0939   |
  | 0.4631        | 3.0   | 4140  | 0.4213          | 0.0942   | 0.0963   |
  | 0.3375        | 4.0   | 5520  | 0.3143          | 0.1044   | 0.0997   |
  | 0.2539        | 5.0   | 6900  | 0.2436          | 0.1091   | 0.1018   |
  | 0.1987        | 6.0   | 8280  | 0.1944          | 0.1098   | 0.1003   |
  | 0.1598        | 7.0   | 9660  | 0.1592          | 0.1094   | 0.0964   |
  | 0.1326        | 8.0   | 11040 | 0.1349          | 0.1097   | 0.0937   |
  | 0.1148        | 9.0   | 12420 | 0.1185          | 0.1089   | 0.0894   |
  | 0.1025        | 10.0  | 13800 | 0.1077          | 0.1066   | 0.0839   |
  | 0.0946        | 11.0  | 15180 | 0.1007          | 0.1030   | 0.0788   |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  