---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-2.5b-1000g
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: nucleotide-transformer-finetuned-lora-NucleotideTransformer
  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. -->

# nucleotide-transformer-finetuned-lora-NucleotideTransformer

This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-2.5b-1000g](https://huggingface.co/InstaDeepAI/nucleotide-transformer-2.5b-1000g) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1687
- F1: 0.9863
- Mcc Score: 0.9686

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|
| 0.2508        | 0.43  | 100  | 0.1791          | 0.9863 | 0.9686    |
| 0.0793        | 0.85  | 200  | 0.4908          | 0.9429 | 0.8814    |
| 0.0408        | 1.28  | 300  | 0.3990          | 0.9600 | 0.9039    |
| 0.0184        | 1.71  | 400  | 0.2259          | 0.9730 | 0.9359    |
| 0.014         | 2.14  | 500  | 0.1308          | 0.9863 | 0.9686    |
| 0.0313        | 2.56  | 600  | 0.1841          | 0.9863 | 0.9686    |
| 0.0162        | 2.99  | 700  | 0.4267          | 0.9730 | 0.9359    |
| 0.0114        | 3.42  | 800  | 0.2700          | 0.9730 | 0.9359    |
| 0.0           | 3.85  | 900  | 0.1612          | 0.9863 | 0.9686    |
| 0.0           | 4.27  | 1000 | 0.1687          | 0.9863 | 0.9686    |


### Framework versions

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