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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