readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: kaelte
    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. -->
  
  # kaelte
  
  This model is a fine-tuned version of [svalabs/gbert-large-zeroshot-nli](https://huggingface.co/svalabs/gbert-large-zeroshot-nli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1126
  - F1: 0.9887
  
  ## Label-Übersetzung
  
  - 0	Freie_Kühlung
  - 1	Kälteanlage_Allgemein
  - 2	Kältemaschine
  - 3	Kältespeicher
  - 4	Rückkühlwerk
  
  
  ## 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: 5e-05
  - train_batch_size: 4
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 0.98  | 46   | 0.3264          | 0.9074 |
  | No log        | 1.98  | 92   | 0.1266          | 0.9590 |
  | No log        | 2.98  | 138  | 0.0603          | 0.9887 |
  | No log        | 3.98  | 184  | 0.1000          | 0.9887 |
  | No log        | 4.98  | 230  | 0.1075          | 0.9887 |
  | No log        | 5.98  | 276  | 0.1091          | 0.9887 |
  | No log        | 6.98  | 322  | 0.1109          | 0.9887 |
  | No log        | 7.98  | 368  | 0.1119          | 0.9887 |
  | No log        | 8.98  | 414  | 0.1124          | 0.9887 |
  | No log        | 9.98  | 460  | 0.1126          | 0.9887 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  