---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-50m-multi-species
tags:
- generated_from_trainer
metrics:
- f1
- matthews_correlation
- accuracy
model-index:
- name: mus_promoter-finetuned-lora-v2-50m-multi-species
  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-v2-50m-multi-species

This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-50m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-50m-multi-species) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1225
- F1: 0.9600
- Matthews Correlation: 0.9039
- Accuracy: 0.9531
- F1 Score: 0.9600

## 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     | Matthews Correlation | Accuracy | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:|
| 0.3569        | 0.43  | 100  | 0.1448          | 0.9275 | 0.8542               | 0.9219   | 0.9275   |
| 0.1828        | 0.85  | 200  | 0.5710          | 0.8955 | 0.8024               | 0.8906   | 0.8955   |
| 0.1894        | 1.28  | 300  | 0.1006          | 0.9863 | 0.9686               | 0.9844   | 0.9863   |
| 0.0543        | 1.71  | 400  | 0.2058          | 0.9589 | 0.9048               | 0.9531   | 0.9589   |
| 0.0932        | 2.14  | 500  | 0.2240          | 0.9600 | 0.9039               | 0.9531   | 0.9600   |
| 0.0431        | 2.56  | 600  | 0.2027          | 0.9474 | 0.8724               | 0.9375   | 0.9474   |
| 0.0381        | 2.99  | 700  | 0.1507          | 0.9600 | 0.9039               | 0.9531   | 0.9600   |
| 0.0167        | 3.42  | 800  | 0.0768          | 0.9863 | 0.9686               | 0.9844   | 0.9863   |
| 0.0158        | 3.85  | 900  | 0.0875          | 0.9730 | 0.9359               | 0.9688   | 0.9730   |
| 0.0265        | 4.27  | 1000 | 0.1225          | 0.9600 | 0.9039               | 0.9531   | 0.9600   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2