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---
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
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