readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: DNADebertaK6_Arabidopsis
    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_Arabidopsis
  
  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: 1.7194
  
  ## 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 |
  |:-------------:|:------:|:------:|:---------------:|
  | 4.6174        | 6.12   | 20000  | 1.9257          |
  | 1.8873        | 12.24  | 40000  | 1.8098          |
  | 1.8213        | 18.36  | 60000  | 1.7952          |
  | 1.8042        | 24.48  | 80000  | 1.7888          |
  | 1.7945        | 30.6   | 100000 | 1.7861          |
  | 1.7873        | 36.72  | 120000 | 1.7772          |
  | 1.782         | 42.84  | 140000 | 1.7757          |
  | 1.7761        | 48.96  | 160000 | 1.7632          |
  | 1.7714        | 55.08  | 180000 | 1.7685          |
  | 1.7677        | 61.2   | 200000 | 1.7568          |
  | 1.7637        | 67.32  | 220000 | 1.7570          |
  | 1.7585        | 73.44  | 240000 | 1.7442          |
  | 1.7554        | 79.56  | 260000 | 1.7556          |
  | 1.7515        | 85.68  | 280000 | 1.7505          |
  | 1.7483        | 91.8   | 300000 | 1.7463          |
  | 1.745         | 97.92  | 320000 | 1.7425          |
  | 1.7427        | 104.04 | 340000 | 1.7425          |
  | 1.7398        | 110.16 | 360000 | 1.7359          |
  | 1.7377        | 116.28 | 380000 | 1.7369          |
  | 1.7349        | 122.4  | 400000 | 1.7340          |
  | 1.7325        | 128.52 | 420000 | 1.7313          |
  | 1.731         | 134.64 | 440000 | 1.7256          |
  | 1.7286        | 140.76 | 460000 | 1.7238          |
  | 1.7267        | 146.88 | 480000 | 1.7324          |
  | 1.7247        | 153.0  | 500000 | 1.7247          |
  | 1.7228        | 159.12 | 520000 | 1.7185          |
  | 1.7209        | 165.24 | 540000 | 1.7166          |
  | 1.7189        | 171.36 | 560000 | 1.7206          |
  | 1.7181        | 177.48 | 580000 | 1.7190          |
  | 1.7159        | 183.6  | 600000 | 1.7194          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  