hyenadna-medium-450k-seqlen-hf_ft_BioS73_1kbpHG19_DHSs_H3K27AC

This model is a fine-tuned version of LongSafari/hyenadna-medium-450k-seqlen-hf on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4797
  • F1 Score: 0.8324
  • Precision: 0.8063
  • Recall: 0.8603
  • Accuracy: 0.8151
  • Auc: 0.8805
  • Prc: 0.8644

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-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Score Precision Recall Accuracy Auc Prc
0.4819 0.3726 500 0.4409 0.8212 0.7769 0.8708 0.7976 0.8718 0.8657
0.4306 0.7452 1000 0.4281 0.8181 0.8103 0.8261 0.8040 0.8826 0.8790
0.4073 1.1177 1500 0.4115 0.8310 0.7977 0.8673 0.8118 0.8884 0.8864
0.3903 1.4903 2000 0.4011 0.8345 0.8096 0.8610 0.8177 0.8902 0.8832
0.3808 1.8629 2500 0.4221 0.8295 0.8075 0.8527 0.8129 0.8865 0.8788
0.3713 2.2355 3000 0.4126 0.8305 0.8212 0.8401 0.8170 0.8959 0.8883
0.3587 2.6080 3500 0.4023 0.8469 0.7937 0.9078 0.8248 0.8936 0.8857
0.3362 2.9806 4000 0.4117 0.8489 0.7852 0.9239 0.8245 0.8925 0.8829
0.3075 3.3532 4500 0.4235 0.8295 0.8120 0.8478 0.8140 0.8946 0.8877
0.319 3.7258 5000 0.4154 0.8497 0.8096 0.8939 0.8312 0.8959 0.8868
0.2986 4.0984 5500 0.4481 0.8377 0.8028 0.8757 0.8189 0.8929 0.8835
0.2712 4.4709 6000 0.4398 0.8281 0.8005 0.8575 0.8099 0.8833 0.8708
0.2819 4.8435 6500 0.4465 0.8324 0.8189 0.8464 0.8181 0.8904 0.8828
0.245 5.2161 7000 0.4827 0.8294 0.8125 0.8471 0.8140 0.8853 0.8713
0.2318 5.5887 7500 0.4797 0.8324 0.8063 0.8603 0.8151 0.8805 0.8644

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.0
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