--- library_name: transformers license: cc-by-nc-sa-4.0 base_model: InstaDeepAI/nucleotide-transformer-v2-250m-multi-species tags: - generated_from_trainer metrics: - precision - recall - accuracy model-index: - name: nucleotide-transformer-v2-250m-multi-species_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot results: [] --- # nucleotide-transformer-v2-250m-multi-species_ft_BioS2_1kbpHG19_DHSs_H3K27AC_one_shot This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-250m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-250m-multi-species) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7399 - F1 Score: 0.8084 - Precision: 0.8006 - Recall: 0.8164 - Accuracy: 0.8013 - Auc: 0.8735 - Prc: 0.8637 ## 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: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 Score | Precision | Recall | Accuracy | Auc | Prc | |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:------:|:------:| | 0.5348 | 0.8403 | 500 | 0.4797 | 0.7964 | 0.7422 | 0.8590 | 0.7744 | 0.8621 | 0.8383 | | 0.3808 | 1.6807 | 1000 | 0.5203 | 0.7973 | 0.8081 | 0.7869 | 0.7946 | 0.8683 | 0.8507 | | 0.2366 | 2.5210 | 1500 | 0.7399 | 0.8084 | 0.8006 | 0.8164 | 0.8013 | 0.8735 | 0.8637 | ### Framework versions - Transformers 4.46.0.dev0 - Pytorch 2.4.1+cu121 - Datasets 2.18.0 - Tokenizers 0.20.0