readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-base-german-cased-finetuned-subj_v6_7Epoch
    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-subj_v6_7Epoch
  
  This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2836
  - Precision: 0.7809
  - Recall: 0.7229
  - F1: 0.7507
  - Accuracy: 0.9107
  
  ## 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: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 33   | 0.3541          | 0.6508    | 0.5486 | 0.5953 | 0.8520   |
  | No log        | 2.0   | 66   | 0.2815          | 0.7492    | 0.6314 | 0.6853 | 0.8836   |
  | No log        | 3.0   | 99   | 0.2659          | 0.7615    | 0.7114 | 0.7356 | 0.9015   |
  | No log        | 4.0   | 132  | 0.2570          | 0.7812    | 0.7343 | 0.7570 | 0.9113   |
  | No log        | 5.0   | 165  | 0.2676          | 0.7672    | 0.7343 | 0.7504 | 0.9084   |
  | No log        | 6.0   | 198  | 0.2791          | 0.7774    | 0.7286 | 0.7522 | 0.9113   |
  | No log        | 7.0   | 231  | 0.2836          | 0.7809    | 0.7229 | 0.7507 | 0.9107   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  