|
--- |
|
license: cc-by-nc-sa-4.0 |
|
base_model: InstaDeepAI/nucleotide-transformer-500m-human-ref |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: mus_promoter-finetuned-lora-NT-500m-human-ref |
|
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. --> |
|
|
|
# mus_promoter-finetuned-lora-NT-500m-human-ref |
|
|
|
This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-500m-human-ref](https://huggingface.co/InstaDeepAI/nucleotide-transformer-500m-human-ref) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4766 |
|
- F1: 0.8732 |
|
- Mcc Score: 0.7192 |
|
- Accuracy: 0.8594 |
|
|
|
## 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: 0.0005 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- training_steps: 1000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Mcc Score | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:| |
|
| 0.7799 | 0.43 | 100 | 0.4819 | 0.8889 | 0.7210 | 0.8594 | |
|
| 0.4117 | 0.85 | 200 | 0.6728 | 0.74 | 0.1475 | 0.5938 | |
|
| 0.352 | 1.28 | 300 | 0.3396 | 0.9014 | 0.7826 | 0.8906 | |
|
| 0.2747 | 1.71 | 400 | 0.3458 | 0.9067 | 0.7750 | 0.8906 | |
|
| 0.2279 | 2.14 | 500 | 0.3053 | 0.9143 | 0.8181 | 0.9062 | |
|
| 0.2304 | 2.56 | 600 | 0.4057 | 0.8919 | 0.7437 | 0.875 | |
|
| 0.1362 | 2.99 | 700 | 0.5446 | 0.8657 | 0.7390 | 0.8594 | |
|
| 0.0391 | 3.42 | 800 | 0.7635 | 0.8889 | 0.7210 | 0.8594 | |
|
| 0.04 | 3.85 | 900 | 0.4871 | 0.9231 | 0.8108 | 0.9062 | |
|
| 0.0333 | 4.27 | 1000 | 0.4766 | 0.8732 | 0.7192 | 0.8594 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.17.1 |
|
- Tokenizers 0.15.2 |
|
|
