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hyenadna-small-32k-seqlen-hf_ft_BioS2_1kbpHG19_DHSs_H3K27AC

This model is a fine-tuned version of LongSafari/hyenadna-small-32k-seqlen-hf on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4638
  • F1 Score: 0.8073
  • Precision: 0.8018
  • Recall: 0.8128
  • Accuracy: 0.7952
  • Auc: 0.8728
  • Prc: 0.8651

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: 8
  • eval_batch_size: 8
  • 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
0.5671 0.0841 500 0.5418 0.7721 0.7343 0.8141 0.7464 0.7985 0.7787
0.5022 0.1683 1000 0.5186 0.7826 0.7680 0.7978 0.7661 0.8279 0.8137
0.5022 0.2524 1500 0.5044 0.8036 0.7154 0.9168 0.7635 0.8360 0.8138
0.4865 0.3366 2000 0.4858 0.7887 0.7708 0.8074 0.7716 0.8440 0.8350
0.4913 0.4207 2500 0.4686 0.8062 0.7560 0.8635 0.7809 0.8553 0.8451
0.472 0.5049 3000 0.4715 0.8107 0.7494 0.8830 0.7824 0.8580 0.8462
0.4776 0.5890 3500 0.4581 0.8064 0.7682 0.8485 0.7849 0.8630 0.8574
0.4571 0.6732 4000 0.4620 0.8162 0.7506 0.8945 0.7874 0.8674 0.8548
0.4702 0.7573 4500 0.4550 0.8009 0.7995 0.8023 0.7895 0.8683 0.8600
0.4533 0.8415 5000 0.4493 0.8121 0.7891 0.8364 0.7957 0.8729 0.8617
0.4401 0.9256 5500 0.4472 0.8134 0.7823 0.8469 0.7949 0.8743 0.8662
0.4505 1.0098 6000 0.4459 0.8100 0.7892 0.8320 0.7940 0.8732 0.8668
0.3944 1.0939 6500 0.4638 0.8073 0.8018 0.8128 0.7952 0.8728 0.8651

Framework versions

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