readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: dnabertregressor
    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. -->
  
  # dnabertregressor
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0140
  - Mse: 0.0140
  - Rmse: 0.1184
  - Mae: 0.0832
  - R2: 0.7870
  - Smape: 35.2829
  
  ## 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: 32
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mse    | Rmse   | Mae    | R2     | Smape   |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------:|
  | No log        | 1.0   | 402  | 0.0396          | 0.0396 | 0.1991 | 0.1457 | 0.3971 | 65.2128 |
  | 0.0535        | 2.0   | 804  | 0.0219          | 0.0219 | 0.1480 | 0.1066 | 0.6671 | 45.3936 |
  | 0.0247        | 3.0   | 1206 | 0.0164          | 0.0164 | 0.1279 | 0.0944 | 0.7511 | 39.7742 |
  | 0.0163        | 4.0   | 1608 | 0.0168          | 0.0168 | 0.1298 | 0.0954 | 0.7438 | 50.0921 |
  | 0.0131        | 5.0   | 2010 | 0.0141          | 0.0141 | 0.1189 | 0.0835 | 0.7848 | 35.9247 |
  | 0.0131        | 6.0   | 2412 | 0.0140          | 0.0140 | 0.1184 | 0.0832 | 0.7870 | 35.2829 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  