File size: 1,882 Bytes
2535d3b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# DNABERT-2-117M_ft_Hepg2_1kbpHG19_DHSs_H3K27AC
This model is a fine-tuned version of [zhihan1996/DNABERT-2-117M](https://huggingface.co/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
|