readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-base-german-cased-finetuned-subj_v5_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_v5_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: 0.3036
  - Precision: 0.7983
  - Recall: 0.7781
  - F1: 0.7881
  - Accuracy: 0.9073
  
  ## 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   | 32   | 0.3438          | 0.6970    | 0.7107 | 0.7038 | 0.8626   |
  | No log        | 2.0   | 64   | 0.2747          | 0.7688    | 0.7472 | 0.7578 | 0.8902   |
  | No log        | 3.0   | 96   | 0.2683          | 0.7827    | 0.7893 | 0.7860 | 0.8981   |
  | No log        | 4.0   | 128  | 0.2768          | 0.8024    | 0.7528 | 0.7768 | 0.9027   |
  | No log        | 5.0   | 160  | 0.2881          | 0.8102    | 0.7556 | 0.7820 | 0.9060   |
  | No log        | 6.0   | 192  | 0.3006          | 0.7959    | 0.7669 | 0.7811 | 0.9040   |
  | No log        | 7.0   | 224  | 0.3036          | 0.7983    | 0.7781 | 0.7881 | 0.9073   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  