readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: 22_12_13_luther_blocks_xl_fp16_5ep
    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. -->
  
  # 22_12_13_luther_blocks_xl_fp16_5ep
  
  This model is a fine-tuned version of [malteos/gpt2-xl-wechsel-german](https://huggingface.co/malteos/gpt2-xl-wechsel-german) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.8833
  - Accuracy: 0.4196
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 0.19  | 50   | 3.0276          | 0.3997   |
  | No log        | 0.38  | 100  | 2.9185          | 0.4143   |
  | No log        | 0.58  | 150  | 2.8846          | 0.4189   |
  | No log        | 0.77  | 200  | 2.8833          | 0.4196   |
  | 3.0309        | 0.96  | 250  | 2.8833          | 0.4196   |
  | 3.0309        | 1.15  | 300  | 2.8833          | 0.4196   |
  | 3.0309        | 1.35  | 350  | 2.8833          | 0.4196   |
  | 3.0309        | 1.54  | 400  | 2.8833          | 0.4196   |
  | 3.0309        | 1.73  | 450  | 2.8833          | 0.4196   |
  | 2.8083        | 1.92  | 500  | 2.8833          | 0.4196   |
  | 2.8083        | 2.12  | 550  | 2.8833          | 0.4196   |
  | 2.8083        | 2.31  | 600  | 2.8833          | 0.4196   |
  | 2.8083        | 2.5   | 650  | 2.8833          | 0.4196   |
  | 2.8083        | 2.69  | 700  | 2.8833          | 0.4196   |
  | 2.7992        | 2.88  | 750  | 2.8833          | 0.4196   |
  | 2.7992        | 3.08  | 800  | 2.8833          | 0.4196   |
  | 2.7992        | 3.27  | 850  | 2.8833          | 0.4196   |
  | 2.7992        | 3.46  | 900  | 2.8833          | 0.4196   |
  | 2.7992        | 3.65  | 950  | 2.8833          | 0.4196   |
  | 2.7935        | 3.85  | 1000 | 2.8833          | 0.4196   |
  | 2.7935        | 4.04  | 1050 | 2.8833          | 0.4196   |
  | 2.7935        | 4.23  | 1100 | 2.8833          | 0.4196   |
  | 2.7935        | 4.42  | 1150 | 2.8833          | 0.4196   |
  | 2.7935        | 4.62  | 1200 | 2.8833          | 0.4196   |
  | 2.8129        | 4.81  | 1250 | 2.8833          | 0.4196   |
  | 2.8129        | 5.0   | 1300 | 2.8833          | 0.4196   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.12.1
  