README.md

metadata

license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-2.5b-1000g
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - accuracy
model-index:
  - name: nucleotide-transformer-2.5b-1000g_ft_Hepg2_1kbpHG19_DHSs_H3K27AC
    results: []

nucleotide-transformer-2.5b-1000g_ft_Hepg2_1kbpHG19_DHSs_H3K27AC

This model is a fine-tuned version of InstaDeepAI/nucleotide-transformer-2.5b-1000g on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4911
• F1 Score: 0.8530
• Precision: 0.9084
• Recall: 0.8041
• Accuracy: 0.8470

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
0.3896	1.8657	500	0.4911	0.8530	0.9084	0.8041	0.8470

Framework versions

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