readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-base-german-cased-noisy-pretrain-fine-tuned_v1.2
    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-noisy-pretrain-fine-tuned_v1.2
  
  This model is a fine-tuned version of [tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v1.2](https://huggingface.co/tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v1.2) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2810
  - Precision: 0.7874
  - Recall: 0.7514
  - F1: 0.7690
  - Accuracy: 0.9147
  
  ## 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   | 0.3078          | 0.7675    | 0.5943 | 0.6699 | 0.8842   |
  | No log        | 2.0   | 66   | 0.2535          | 0.7729    | 0.7486 | 0.7605 | 0.9073   |
  | No log        | 3.0   | 99   | 0.2417          | 0.7714    | 0.7714 | 0.7714 | 0.9119   |
  | No log        | 4.0   | 132  | 0.2532          | 0.8031    | 0.7343 | 0.7672 | 0.9142   |
  | No log        | 5.0   | 165  | 0.2675          | 0.7834    | 0.7543 | 0.7686 | 0.9142   |
  | No log        | 6.0   | 198  | 0.2750          | 0.7870    | 0.76   | 0.7733 | 0.9159   |
  | No log        | 7.0   | 231  | 0.2810          | 0.7874    | 0.7514 | 0.7690 | 0.9147   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  