readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: PromoGen_K562_2080Ti_restart
    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. -->
  
  # PromoGen_K562_2080Ti_restart
  
  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: 0.4624
  
  ## 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: 0.0005
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 25
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss |
  |:-------------:|:-----:|:------:|:---------------:|
  | 0.7676        | 0.49  | 2500   | 0.7383          |
  | 0.7121        | 0.97  | 5000   | 0.6867          |
  | 0.6914        | 1.46  | 7500   | 0.6705          |
  | 0.6837        | 1.95  | 10000  | 0.6622          |
  | 0.6778        | 2.44  | 12500  | 0.6558          |
  | 0.6748        | 2.92  | 15000  | 0.6517          |
  | 0.6676        | 3.41  | 17500  | 0.6433          |
  | 0.6593        | 3.9   | 20000  | 0.6358          |
  | 0.6584        | 4.38  | 22500  | 0.6320          |
  | 0.6557        | 4.87  | 25000  | 0.6301          |
  | 0.6523        | 5.36  | 27500  | 0.6257          |
  | 0.6478        | 5.84  | 30000  | 0.6236          |
  | 0.6393        | 6.33  | 32500  | 0.6145          |
  | 0.6039        | 6.82  | 35000  | 0.5658          |
  | 0.5616        | 7.31  | 37500  | 0.5376          |
  | 0.5518        | 7.79  | 40000  | 0.5310          |
  | 0.5509        | 8.28  | 42500  | 0.5273          |
  | 0.5487        | 8.77  | 45000  | 0.5261          |
  | 0.5479        | 9.25  | 47500  | 0.5249          |
  | 0.546         | 9.74  | 50000  | 0.5242          |
  | 0.5447        | 10.23 | 52500  | 0.5229          |
  | 0.5439        | 10.71 | 55000  | 0.5220          |
  | 0.5433        | 11.2  | 57500  | 0.5209          |
  | 0.5394        | 11.69 | 60000  | 0.5162          |
  | 0.5153        | 12.18 | 62500  | 0.4944          |
  | 0.5137        | 12.66 | 65000  | 0.4932          |
  | 0.514         | 13.15 | 67500  | 0.4924          |
  | 0.5131        | 13.64 | 70000  | 0.4919          |
  | 0.5104        | 14.12 | 72500  | 0.4914          |
  | 0.5122        | 14.61 | 75000  | 0.4906          |
  | 0.5089        | 15.1  | 77500  | 0.4901          |
  | 0.5076        | 15.59 | 80000  | 0.4891          |
  | 0.4986        | 16.07 | 82500  | 0.4721          |
  | 0.4875        | 16.56 | 85000  | 0.4672          |
  | 0.4887        | 17.05 | 87500  | 0.4669          |
  | 0.4839        | 17.53 | 90000  | 0.4661          |
  | 0.4849        | 18.02 | 92500  | 0.4654          |
  | 0.4848        | 18.51 | 95000  | 0.4649          |
  | 0.4831        | 18.99 | 97500  | 0.4646          |
  | 0.4816        | 19.48 | 100000 | 0.4644          |
  | 0.4808        | 19.97 | 102500 | 0.4637          |
  | 0.4812        | 20.46 | 105000 | 0.4634          |
  | 0.4813        | 20.94 | 107500 | 0.4633          |
  | 0.4818        | 21.43 | 110000 | 0.4631          |
  | 0.4813        | 21.92 | 112500 | 0.4629          |
  | 0.4782        | 22.4  | 115000 | 0.4628          |
  | 0.4804        | 22.89 | 117500 | 0.4626          |
  | 0.4815        | 23.38 | 120000 | 0.4625          |
  | 0.4812        | 23.87 | 122500 | 0.4625          |
  | 0.4785        | 24.35 | 125000 | 0.4624          |
  | 0.4795        | 24.84 | 127500 | 0.4624          |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0
  - Datasets 2.7.0
  - Tokenizers 0.13.0.dev0
  