metadata
base_model: zhihan1996/DNABERT-2-117M
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: DNABERT-2-117M_ft_Hepg2_1kbpHG19_DHSs_H3K27AC
results: []
DNABERT-2-117M_ft_Hepg2_1kbpHG19_DHSs_H3K27AC
This model is a fine-tuned version of zhihan1996/DNABERT-2-117M on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4809
- F1 Score: 0.8080
- Precision: 0.7661
- Recall: 0.8546
- Accuracy: 0.7770
- Mcc Score: 0.5487
- Roc Auc Score: 0.7686
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: 32
- eval_batch_size: 32
- 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 | Mcc Score | Roc Auc Score |
|---|---|---|---|---|---|---|---|---|---|
| 0.4948 | 1.4881 | 500 | 0.5034 | 0.7825 | 0.7980 | 0.7677 | 0.7658 | 0.5296 | 0.7656 |
| 0.4623 | 2.9762 | 1000 | 0.4809 | 0.8080 | 0.7661 | 0.8546 | 0.7770 | 0.5487 | 0.7686 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.0