---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-500m-multi-species
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: mus_promoter-finetuned-lora-NT-v2-500m-ms
  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-v2-500m-ms

This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-500m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-500m-multi-species) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1042
- F1: 0.9863
- Mcc Score: 0.9686
- Accuracy: 0.9844

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.5534        | 0.43  | 100  | 0.5989          | 0.8824 | 0.7646    | 0.875    |
| 0.3298        | 0.85  | 200  | 0.1327          | 0.9730 | 0.9359    | 0.9688   |
| 0.1827        | 1.28  | 300  | 0.0652          | 0.9867 | 0.9683    | 0.9844   |
| 0.2014        | 1.71  | 400  | 0.2227          | 0.9600 | 0.9039    | 0.9531   |
| 0.1183        | 2.14  | 500  | 0.0556          | 0.9863 | 0.9686    | 0.9844   |
| 0.1052        | 2.56  | 600  | 0.2231          | 0.9577 | 0.9094    | 0.9531   |
| 0.0781        | 2.99  | 700  | 0.1219          | 0.9730 | 0.9359    | 0.9688   |
| 0.0477        | 3.42  | 800  | 0.1048          | 0.9863 | 0.9686    | 0.9844   |
| 0.025         | 3.85  | 900  | 0.0978          | 0.9863 | 0.9686    | 0.9844   |
| 0.0221        | 4.27  | 1000 | 0.1042          | 0.9863 | 0.9686    | 0.9844   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2