readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: DNADebertaK6_Worm
    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. -->
  
  # DNADebertaK6_Worm
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6161
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - training_steps: 600001
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step   | Validation Loss |
  |:-------------:|:------:|:------:|:---------------:|
  | 4.5653        | 7.26   | 20000  | 1.8704          |
  | 1.8664        | 14.53  | 40000  | 1.7762          |
  | 1.7803        | 21.79  | 60000  | 1.7429          |
  | 1.7502        | 29.06  | 80000  | 1.7305          |
  | 1.7329        | 36.32  | 100000 | 1.7185          |
  | 1.7191        | 43.59  | 120000 | 1.7073          |
  | 1.7065        | 50.85  | 140000 | 1.6925          |
  | 1.6945        | 58.12  | 160000 | 1.6877          |
  | 1.6862        | 65.38  | 180000 | 1.6792          |
  | 1.6788        | 72.65  | 200000 | 1.6712          |
  | 1.6729        | 79.91  | 220000 | 1.6621          |
  | 1.6679        | 87.18  | 240000 | 1.6608          |
  | 1.6632        | 94.44  | 260000 | 1.6586          |
  | 1.6582        | 101.71 | 280000 | 1.6585          |
  | 1.6551        | 108.97 | 300000 | 1.6564          |
  | 1.6507        | 116.24 | 320000 | 1.6449          |
  | 1.6481        | 123.5  | 340000 | 1.6460          |
  | 1.6448        | 130.77 | 360000 | 1.6411          |
  | 1.6425        | 138.03 | 380000 | 1.6408          |
  | 1.6387        | 145.3  | 400000 | 1.6358          |
  | 1.6369        | 152.56 | 420000 | 1.6373          |
  | 1.6337        | 159.83 | 440000 | 1.6364          |
  | 1.6312        | 167.09 | 460000 | 1.6303          |
  | 1.6298        | 174.36 | 480000 | 1.6346          |
  | 1.6273        | 181.62 | 500000 | 1.6272          |
  | 1.6244        | 188.88 | 520000 | 1.6268          |
  | 1.6225        | 196.15 | 540000 | 1.6295          |
  | 1.6207        | 203.41 | 560000 | 1.6206          |
  | 1.6186        | 210.68 | 580000 | 1.6277          |
  | 1.6171        | 217.94 | 600000 | 1.6161          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  