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hyenadna-medium-160k-seqlen-hf_ft_BioS45_1kbpHG19_DHSs_H3K27AC

This model is a fine-tuned version of LongSafari/hyenadna-medium-160k-seqlen-hf on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5104
  • F1 Score: 0.8100
  • Precision: 0.8002
  • Recall: 0.8202
  • Accuracy: 0.7993
  • Auc: 0.8765
  • Prc: 0.8748

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
0.5145 0.4205 500 0.4663 0.7945 0.8003 0.7887 0.7871 0.8575 0.8420
0.4678 0.8410 1000 0.4667 0.8075 0.7334 0.8984 0.7766 0.8691 0.8628
0.4586 1.2616 1500 0.4759 0.8157 0.7463 0.8992 0.7880 0.8674 0.8598
0.4467 1.6821 2000 0.4349 0.8134 0.7961 0.8315 0.8010 0.8798 0.8751
0.4298 2.1026 2500 0.4558 0.8170 0.7480 0.9 0.7897 0.8749 0.8679
0.4068 2.5231 3000 0.4374 0.7982 0.8139 0.7831 0.7934 0.8830 0.8793
0.4299 2.9437 3500 0.4358 0.8117 0.8033 0.8202 0.8014 0.8816 0.8787
0.3994 3.3642 4000 0.4543 0.8120 0.8287 0.7960 0.8077 0.8815 0.8781
0.3742 3.7847 4500 0.4463 0.8139 0.7948 0.8339 0.8010 0.8796 0.8733
0.345 4.2052 5000 0.5104 0.8100 0.8002 0.8202 0.7993 0.8765 0.8748

Framework versions

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