readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: DNADebertaSentencepiece30k_continuation_continuation
    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. -->
  
  # DNADebertaSentencepiece30k_continuation_continuation
  
  This model is a fine-tuned version of [Vlasta/DNADebertaSentencepiece30k_continuation](https://huggingface.co/Vlasta/DNADebertaSentencepiece30k_continuation) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 5.9867
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss |
  |:-------------:|:-----:|:------:|:---------------:|
  | 6.1786        | 0.41  | 5000   | 6.1475          |
  | 6.1856        | 0.81  | 10000  | 6.1490          |
  | 6.1769        | 1.22  | 15000  | 6.1370          |
  | 6.1714        | 1.62  | 20000  | 6.1330          |
  | 6.1633        | 2.03  | 25000  | 6.1221          |
  | 6.1548        | 2.44  | 30000  | 6.1180          |
  | 6.1495        | 2.84  | 35000  | 6.1141          |
  | 6.1453        | 3.25  | 40000  | 6.1026          |
  | 6.1362        | 3.66  | 45000  | 6.0984          |
  | 6.1325        | 4.06  | 50000  | 6.0961          |
  | 6.1227        | 4.47  | 55000  | 6.0874          |
  | 6.1215        | 4.87  | 60000  | 6.0806          |
  | 6.1149        | 5.28  | 65000  | 6.0779          |
  | 6.1099        | 5.69  | 70000  | 6.0701          |
  | 6.104         | 6.09  | 75000  | 6.0633          |
  | 6.0963        | 6.5   | 80000  | 6.0628          |
  | 6.095         | 6.91  | 85000  | 6.0572          |
  | 6.0858        | 7.31  | 90000  | 6.0525          |
  | 6.0895        | 7.72  | 95000  | 6.0430          |
  | 6.0804        | 8.12  | 100000 | 6.0437          |
  | 6.0767        | 8.53  | 105000 | 6.0371          |
  | 6.0748        | 8.94  | 110000 | 6.0312          |
  | 6.0702        | 9.34  | 115000 | 6.0293          |
  | 6.0668        | 9.75  | 120000 | 6.0242          |
  | 6.0615        | 10.16 | 125000 | 6.0213          |
  | 6.0568        | 10.56 | 130000 | 6.0183          |
  | 6.0552        | 10.97 | 135000 | 6.0125          |
  | 6.0496        | 11.37 | 140000 | 6.0087          |
  | 6.0493        | 11.78 | 145000 | 6.0084          |
  | 6.0466        | 12.19 | 150000 | 6.0060          |
  | 6.042         | 12.59 | 155000 | 6.0008          |
  | 6.0375        | 13.0  | 160000 | 5.9986          |
  | 6.0345        | 13.41 | 165000 | 5.9940          |
  | 6.0336        | 13.81 | 170000 | 5.9905          |
  | 6.0334        | 14.22 | 175000 | 5.9891          |
  | 6.0313        | 14.62 | 180000 | 5.9887          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  