readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-base-german-cased-finetuned-subj_v5_11Epoch
    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_11Epoch
  
  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: 0.3467
  - Precision: 0.8240
  - Recall: 0.8287
  - F1: 0.8263
  - Accuracy: 0.9198
  
  ## 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: 11
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 32   | 0.3485          | 0.6992    | 0.7051 | 0.7021 | 0.8639   |
  | No log        | 2.0   | 64   | 0.2679          | 0.7947    | 0.7612 | 0.7776 | 0.8994   |
  | No log        | 3.0   | 96   | 0.2555          | 0.8073    | 0.8118 | 0.8095 | 0.9112   |
  | No log        | 4.0   | 128  | 0.2591          | 0.8290    | 0.8034 | 0.8160 | 0.9132   |
  | No log        | 5.0   | 160  | 0.2808          | 0.8450    | 0.8118 | 0.8281 | 0.9158   |
  | No log        | 6.0   | 192  | 0.2953          | 0.8386    | 0.8174 | 0.8279 | 0.9172   |
  | No log        | 7.0   | 224  | 0.3164          | 0.8347    | 0.8371 | 0.8359 | 0.9204   |
  | No log        | 8.0   | 256  | 0.3267          | 0.8329    | 0.8258 | 0.8293 | 0.9178   |
  | No log        | 9.0   | 288  | 0.3373          | 0.8268    | 0.8315 | 0.8291 | 0.9198   |
  | No log        | 10.0  | 320  | 0.3450          | 0.8324    | 0.8230 | 0.8277 | 0.9211   |
  | No log        | 11.0  | 352  | 0.3467          | 0.8240    | 0.8287 | 0.8263 | 0.9198   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  