readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: genome-bert
    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. -->
  
  # genome-bert
  
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4267
  
  ## 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: 0.0001
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 256
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_steps: 400
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 0.5187        | 0.65  | 1000  | 0.6013          |
  | 0.4429        | 1.31  | 2000  | 0.5585          |
  | 0.3791        | 1.96  | 3000  | 0.5298          |
  | 0.3316        | 2.62  | 4000  | 0.5153          |
  | 0.2991        | 3.27  | 5000  | 0.5025          |
  | 0.3066        | 3.93  | 6000  | 0.4808          |
  | 0.2795        | 4.58  | 7000  | 0.4675          |
  | 0.2599        | 5.24  | 8000  | 0.4594          |
  | 0.2432        | 5.89  | 9000  | 0.4460          |
  | 0.2282        | 6.54  | 10000 | 0.4431          |
  | 0.2167        | 7.2   | 11000 | 0.4381          |
  | 0.2075        | 7.85  | 12000 | 0.4291          |
  | 0.2013        | 8.51  | 13000 | 0.4307          |
  | 0.1977        | 9.16  | 14000 | 0.4266          |
  | 0.1951        | 9.82  | 15000 | 0.4267          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  