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---
library_name: peft
license: bsd-3-clause
base_model: hugohrban/progen2-base
tags:
- generated_from_trainer
model-index:
- name: Progen2_Kinase_PhosphositeGen_dkz_traindata
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. -->
# Progen2_Kinase_PhosphositeGen_dkz_traindata
This model is a fine-tuned version of [hugohrban/progen2-base](https://huggingface.co/hugohrban/progen2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0955
- Perplexity: 8.1296
## 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: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 5000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Perplexity |
|:-------------:|:------:|:----:|:---------------:|:----------:|
| 4.7229 | 0.1455 | 100 | 2.1862 | 8.9015 |
| 4.2858 | 0.2909 | 200 | 2.1091 | 8.2405 |
| 4.2112 | 0.4364 | 300 | 2.0519 | 7.7824 |
| 4.1146 | 0.5818 | 400 | 2.0049 | 7.4252 |
| 4.0772 | 0.7273 | 500 | 1.9859 | 7.2855 |
| 3.9871 | 0.8727 | 600 | 1.9478 | 7.0130 |
| 3.891 | 1.0175 | 700 | 1.9204 | 6.8236 |
| 3.4841 | 1.1629 | 800 | 1.8889 | 6.6122 |
| 3.4596 | 1.3084 | 900 | 1.8696 | 6.4854 |
| 3.4659 | 1.4538 | 1000 | 1.8430 | 6.3152 |
| 3.433 | 1.5993 | 1100 | 1.8105 | 6.1137 |
| 3.3728 | 1.7447 | 1200 | 1.7991 | 6.0441 |
| 3.3853 | 1.8902 | 1300 | 1.7924 | 6.0040 |
| 3.1832 | 2.0349 | 1400 | 1.7975 | 6.0348 |
| 2.8198 | 2.1804 | 1500 | 1.7924 | 6.0041 |
| 2.7867 | 2.3258 | 1600 | 1.7604 | 5.8149 |
| 2.8669 | 2.4713 | 1700 | 1.7437 | 5.7183 |
| 2.795 | 2.6167 | 1800 | 1.7307 | 5.6445 |
| 2.8152 | 2.7622 | 1900 | 1.7188 | 5.5779 |
| 2.7734 | 2.9076 | 2000 | 1.6911 | 5.4256 |
| 2.5299 | 3.0524 | 2100 | 1.7682 | 5.8605 |
| 2.2126 | 3.1978 | 2200 | 1.7346 | 5.6669 |
| 2.2435 | 3.3433 | 2300 | 1.7104 | 5.5310 |
| 2.2663 | 3.4887 | 2400 | 1.7144 | 5.5536 |
| 2.2463 | 3.6342 | 2500 | 1.7338 | 5.6620 |
| 2.3117 | 3.7796 | 2600 | 1.6879 | 5.4079 |
| 2.2655 | 3.9251 | 2700 | 1.6946 | 5.4447 |
| 1.9936 | 4.0698 | 2800 | 1.8444 | 6.3244 |
| 1.7929 | 4.2153 | 2900 | 1.8653 | 6.4577 |
| 1.8214 | 4.3607 | 3000 | 1.7600 | 5.8123 |
| 1.8505 | 4.5062 | 3100 | 1.7855 | 5.9628 |
| 1.8382 | 4.6516 | 3200 | 1.7955 | 6.0225 |
| 1.7945 | 4.7971 | 3300 | 1.7754 | 5.9028 |
| 1.8238 | 4.9425 | 3400 | 1.7820 | 5.9418 |
| 1.573 | 5.0873 | 3500 | 1.8691 | 6.4823 |
| 1.4562 | 5.2327 | 3600 | 1.8905 | 6.6225 |
| 1.47 | 5.3782 | 3700 | 2.0037 | 7.4163 |
| 1.4649 | 5.5236 | 3800 | 1.8911 | 6.6268 |
| 1.4778 | 5.6691 | 3900 | 1.9307 | 6.8940 |
| 1.4985 | 5.8145 | 4000 | 1.9265 | 6.8655 |
| 1.4587 | 5.96 | 4100 | 1.9128 | 6.7720 |
| 1.258 | 6.1047 | 4200 | 2.0383 | 7.6773 |
| 1.2239 | 6.2502 | 4300 | 2.0444 | 7.7244 |
| 1.2186 | 6.3956 | 4400 | 2.0497 | 7.7658 |
| 1.2174 | 6.5411 | 4500 | 2.0454 | 7.7323 |
| 1.2051 | 6.6865 | 4600 | 2.0195 | 7.5345 |
| 1.2189 | 6.832 | 4700 | 2.0461 | 7.7376 |
| 1.2061 | 6.9775 | 4800 | 2.0435 | 7.7176 |
| 1.0575 | 7.1222 | 4900 | 2.0885 | 8.0727 |
| 1.048 | 7.2676 | 5000 | 2.0955 | 8.1296 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.47.1
- Pytorch 2.1.0.post301
- Datasets 3.0.2
- Tokenizers 0.21.0 |