PeptideGPT
Collection
This collection hosts all the PeptideGPT models for four properties of proteins - hemolytic, non-hemolytic, non-fouling and solubility.
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4 items
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Updated
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2
output_sol_3
This model is a fine-tuned version of nferruz/ProtGPT2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.6849
- Accuracy: 0.2249
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: 1e-06
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.7291 | 1.0 | 387 | 6.4419 | 0.1754 |
| 6.5666 | 2.0 | 774 | 6.2737 | 0.1847 |
| 6.4479 | 3.0 | 1161 | 6.1396 | 0.1918 |
| 6.3439 | 4.0 | 1548 | 6.0359 | 0.1974 |
| 6.2577 | 5.0 | 1935 | 5.9318 | 0.2031 |
| 6.172 | 6.0 | 2322 | 5.8617 | 0.2083 |
| 6.0943 | 7.0 | 2709 | 5.8212 | 0.2115 |
| 6.0318 | 8.0 | 3096 | 5.7983 | 0.2132 |
| 5.9812 | 9.0 | 3483 | 5.7818 | 0.2151 |
| 5.9436 | 10.0 | 3870 | 5.7673 | 0.2163 |
| 5.9144 | 11.0 | 4257 | 5.7563 | 0.2171 |
| 5.8923 | 12.0 | 4644 | 5.7452 | 0.2185 |
| 5.8723 | 13.0 | 5031 | 5.7387 | 0.2190 |
| 5.8549 | 14.0 | 5418 | 5.7320 | 0.2193 |
| 5.8427 | 15.0 | 5805 | 5.7259 | 0.2199 |
| 5.8306 | 16.0 | 6192 | 5.7219 | 0.2203 |
| 5.8176 | 17.0 | 6579 | 5.7186 | 0.2204 |
| 5.8129 | 18.0 | 6966 | 5.7153 | 0.2206 |
| 5.8055 | 19.0 | 7353 | 5.7119 | 0.2211 |
| 5.7954 | 20.0 | 7740 | 5.7097 | 0.2213 |
| 5.7906 | 21.0 | 8127 | 5.7078 | 0.2219 |
| 5.7834 | 22.0 | 8514 | 5.7061 | 0.2221 |
| 5.7779 | 23.0 | 8901 | 5.7042 | 0.2224 |
| 5.7718 | 24.0 | 9288 | 5.7019 | 0.2226 |
| 5.7664 | 25.0 | 9675 | 5.7002 | 0.2231 |
| 5.7616 | 26.0 | 10062 | 5.6989 | 0.2234 |
| 5.7596 | 27.0 | 10449 | 5.6972 | 0.2234 |
| 5.7553 | 28.0 | 10836 | 5.6960 | 0.2236 |
| 5.7525 | 29.0 | 11223 | 5.6948 | 0.2235 |
| 5.7488 | 30.0 | 11610 | 5.6939 | 0.2236 |
| 5.7445 | 31.0 | 11997 | 5.6930 | 0.2237 |
| 5.7409 | 32.0 | 12384 | 5.6919 | 0.2237 |
| 5.7389 | 33.0 | 12771 | 5.6912 | 0.2237 |
| 5.739 | 34.0 | 13158 | 5.6904 | 0.2239 |
| 5.7339 | 35.0 | 13545 | 5.6896 | 0.2239 |
| 5.731 | 36.0 | 13932 | 5.6891 | 0.2240 |
| 5.7285 | 37.0 | 14319 | 5.6885 | 0.2240 |
| 5.724 | 38.0 | 14706 | 5.6881 | 0.2241 |
| 5.7241 | 39.0 | 15093 | 5.6874 | 0.2242 |
| 5.724 | 40.0 | 15480 | 5.6871 | 0.2244 |
| 5.7199 | 41.0 | 15867 | 5.6867 | 0.2245 |
| 5.7212 | 42.0 | 16254 | 5.6863 | 0.2244 |
| 5.7209 | 43.0 | 16641 | 5.6859 | 0.2245 |
| 5.7169 | 44.0 | 17028 | 5.6857 | 0.2245 |
| 5.7185 | 45.0 | 17415 | 5.6856 | 0.2247 |
| 5.7165 | 46.0 | 17802 | 5.6853 | 0.2247 |
| 5.7202 | 47.0 | 18189 | 5.6851 | 0.2248 |
| 5.7183 | 48.0 | 18576 | 5.6850 | 0.2248 |
| 5.7179 | 49.0 | 18963 | 5.6849 | 0.2248 |
| 5.7164 | 50.0 | 19350 | 5.6849 | 0.2249 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1
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Model tree for aayush14/PeptideGPT_soluble
Base model
nferruz/ProtGPT2