---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-500m-multi-species
tags:
- generated_from_trainer
metrics:
- f1
- matthews_correlation
- accuracy
model-index:
- name: gut_6000-finetuned-lora-NT-v2-500m-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. -->

# gut_6000-finetuned-lora-NT-v2-500m-multi-species

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: 0.4765
- F1: 0.8404
- Matthews Correlation: 0.5698
- Accuracy: 0.7956
- F1 Score: 0.8404

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:|
| 0.7596        | 0.02  | 100  | 0.7104          | 0.0744 | -0.1826              | 0.3695   | 0.0744   |
| 0.6692        | 0.04  | 200  | 0.6143          | 0.7828 | 0.3311               | 0.6803   | 0.7828   |
| 0.6022        | 0.05  | 300  | 0.5708          | 0.8180 | 0.4877               | 0.7563   | 0.8180   |
| 0.5577        | 0.07  | 400  | 0.5906          | 0.8080 | 0.5037               | 0.7639   | 0.8080   |
| 0.5743        | 0.09  | 500  | 0.5789          | 0.7710 | 0.2695               | 0.6470   | 0.7710   |
| 0.5052        | 0.11  | 600  | 0.5010          | 0.8273 | 0.5450               | 0.7842   | 0.8273   |
| 0.5012        | 0.12  | 700  | 0.4926          | 0.8409 | 0.5575               | 0.7842   | 0.8409   |
| 0.4757        | 0.14  | 800  | 0.4827          | 0.8368 | 0.5588               | 0.7905   | 0.8368   |
| 0.5166        | 0.16  | 900  | 0.4715          | 0.8470 | 0.5778               | 0.7948   | 0.8470   |
| 0.4667        | 0.18  | 1000 | 0.4765          | 0.8404 | 0.5698               | 0.7956   | 0.8404   |


### Framework versions

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