readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: DNADebertaK6_Fruitfly
    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_Fruitfly
  
  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: 1.7137
  
  ## 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 |
  |:-------------:|:------:|:------:|:---------------:|
  | 4.5584        | 5.36   | 20000  | 1.9795          |
  | 1.9682        | 10.73  | 40000  | 1.8618          |
  | 1.8692        | 16.09  | 60000  | 1.8273          |
  | 1.8339        | 21.45  | 80000  | 1.8076          |
  | 1.8208        | 26.82  | 100000 | 1.8073          |
  | 1.8105        | 32.18  | 120000 | 1.7925          |
  | 1.8022        | 37.54  | 140000 | 1.7909          |
  | 1.7955        | 42.91  | 160000 | 1.7836          |
  | 1.7907        | 48.27  | 180000 | 1.7769          |
  | 1.7849        | 53.63  | 200000 | 1.7755          |
  | 1.7805        | 59.0   | 220000 | 1.7677          |
  | 1.7769        | 64.36  | 240000 | 1.7690          |
  | 1.7723        | 69.72  | 260000 | 1.7614          |
  | 1.7689        | 75.09  | 280000 | 1.7586          |
  | 1.7646        | 80.45  | 300000 | 1.7523          |
  | 1.7607        | 85.81  | 320000 | 1.7484          |
  | 1.7572        | 91.18  | 340000 | 1.7458          |
  | 1.754         | 96.54  | 360000 | 1.7460          |
  | 1.7498        | 101.9  | 380000 | 1.7326          |
  | 1.7463        | 107.27 | 400000 | 1.7377          |
  | 1.7438        | 112.63 | 420000 | 1.7318          |
  | 1.7406        | 117.99 | 440000 | 1.7342          |
  | 1.7383        | 123.36 | 460000 | 1.7339          |
  | 1.7348        | 128.72 | 480000 | 1.7244          |
  | 1.7324        | 134.08 | 500000 | 1.7236          |
  | 1.7289        | 139.45 | 520000 | 1.7155          |
  | 1.7268        | 144.81 | 540000 | 1.7254          |
  | 1.725         | 150.17 | 560000 | 1.7191          |
  | 1.7221        | 155.54 | 580000 | 1.7147          |
  | 1.7209        | 160.9  | 600000 | 1.7137          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  