metadata
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-50m-multi-species
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: >-
nucleotide-transformer-v2-50m-multi-species_ft_BioS73_1kbpHG19_DHSs_H3K27AC_one_shot
results: []
nucleotide-transformer-v2-50m-multi-species_ft_BioS73_1kbpHG19_DHSs_H3K27AC_one_shot
This model is a fine-tuned version of InstaDeepAI/nucleotide-transformer-v2-50m-multi-species on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3612
- F1 Score: 0.7143
- Precision: 0.625
- Recall: 0.8333
- Accuracy: 0.7037
- Auc: 0.7944
- Prc: 0.7771
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.1151 | 18.5185 | 500 | 1.3612 | 0.7143 | 0.625 | 0.8333 | 0.7037 | 0.7944 | 0.7771 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.18.0
- Tokenizers 0.20.0