readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-german-cased-finetuned-tagesschau-subcategories
    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. -->
  
  # distilbert-base-german-cased-finetuned-tagesschau-subcategories
  
  This model is a fine-tuned version of [distilbert-base-german-cased](https://huggingface.co/distilbert-base-german-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5230
  - Accuracy: 0.8267
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 0.4   | 30   | 1.5130          | 0.5733   |
  | No log        | 0.8   | 60   | 1.0629          | 0.7133   |
  | No log        | 1.2   | 90   | 0.8431          | 0.76     |
  | No log        | 1.6   | 120  | 0.7812          | 0.7467   |
  | No log        | 2.0   | 150  | 0.6373          | 0.78     |
  | No log        | 2.4   | 180  | 0.5567          | 0.8133   |
  | No log        | 2.8   | 210  | 0.5650          | 0.8067   |
  | No log        | 3.2   | 240  | 0.5068          | 0.8267   |
  | No log        | 3.6   | 270  | 0.5230          | 0.8267   |
  | No log        | 4.0   | 300  | 0.5318          | 0.8133   |
  | No log        | 4.4   | 330  | 0.5327          | 0.8067   |
  | No log        | 4.8   | 360  | 0.4918          | 0.82     |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  