readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: DNADebertaSentencepiece30k_continuation_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_continuation
  
  This model is a fine-tuned version of [Vlasta/DNADebertaSentencepiece30k_continuation_continuation](https://huggingface.co/Vlasta/DNADebertaSentencepiece30k_continuation_continuation) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 5.9319
  
  ## 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 |
  |:-------------:|:-----:|:------:|:---------------:|
  | 6.0844        | 0.41  | 5000   | 6.0623          |
  | 6.0962        | 0.81  | 10000  | 6.0659          |
  | 6.0903        | 1.22  | 15000  | 6.0566          |
  | 6.0874        | 1.62  | 20000  | 6.0550          |
  | 6.082         | 2.03  | 25000  | 6.0485          |
  | 6.0756        | 2.44  | 30000  | 6.0446          |
  | 6.0722        | 2.84  | 35000  | 6.0429          |
  | 6.0698        | 3.25  | 40000  | 6.0317          |
  | 6.0627        | 3.66  | 45000  | 6.0297          |
  | 6.0606        | 4.06  | 50000  | 6.0301          |
  | 6.0521        | 4.47  | 55000  | 6.0224          |
  | 6.0526        | 4.87  | 60000  | 6.0159          |
  | 6.0473        | 5.28  | 65000  | 6.0140          |
  | 6.0435        | 5.69  | 70000  | 6.0076          |
  | 6.039         | 6.09  | 75000  | 6.0022          |
  | 6.032         | 6.5   | 80000  | 6.0037          |
  | 6.0319        | 6.91  | 85000  | 5.9979          |
  | 6.0232        | 7.31  | 90000  | 5.9937          |
  | 6.0279        | 7.72  | 95000  | 5.9844          |
  | 6.0198        | 8.12  | 100000 | 5.9854          |
  | 6.0165        | 8.53  | 105000 | 5.9796          |
  | 6.0153        | 8.94  | 110000 | 5.9741          |
  | 6.0111        | 9.34  | 115000 | 5.9722          |
  | 6.0082        | 9.75  | 120000 | 5.9679          |
  | 6.0035        | 10.16 | 125000 | 5.9654          |
  | 5.999         | 10.56 | 130000 | 5.9624          |
  | 5.998         | 10.97 | 135000 | 5.9572          |
  | 5.9926        | 11.37 | 140000 | 5.9535          |
  | 5.9927        | 11.78 | 145000 | 5.9533          |
  | 5.9903        | 12.19 | 150000 | 5.9517          |
  | 5.986         | 12.59 | 155000 | 5.9459          |
  | 5.9816        | 13.0  | 160000 | 5.9439          |
  | 5.9786        | 13.41 | 165000 | 5.9390          |
  | 5.9781        | 13.81 | 170000 | 5.9357          |
  | 5.9779        | 14.22 | 175000 | 5.9346          |
  | 5.9756        | 14.62 | 180000 | 5.9339          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  