---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-250m-multi-species
tags:
- generated_from_trainer
metrics:
- f1
- matthews_correlation
- accuracy
model-index:
- name: gut_1024b-finetuned-lora-v2-250m-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_1024b-finetuned-lora-v2-250m-multi-species

This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-250m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-250m-multi-species) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4815
- F1: 0.8414
- Matthews Correlation: 0.5610
- Accuracy: 0.7880
- F1 Score: 0.8414

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:|
| 0.682         | 0.02  | 100  | 0.5545          | 0.8132 | 0.4597               | 0.7369   | 0.8132   |
| 0.6379        | 0.04  | 200  | 0.6119          | 0.7498 | 0.4244               | 0.7154   | 0.7498   |
| 0.5973        | 0.05  | 300  | 0.5226          | 0.8221 | 0.5154               | 0.7707   | 0.8221   |
| 0.5451        | 0.07  | 400  | 0.5159          | 0.8244 | 0.5010               | 0.7521   | 0.8244   |
| 0.5538        | 0.09  | 500  | 0.5538          | 0.8102 | 0.5043               | 0.7648   | 0.8102   |
| 0.549         | 0.11  | 600  | 0.5220          | 0.8258 | 0.5188               | 0.7715   | 0.8258   |
| 0.4887        | 0.12  | 700  | 0.4940          | 0.8330 | 0.5317               | 0.7728   | 0.8330   |
| 0.4893        | 0.14  | 800  | 0.4951          | 0.8352 | 0.5519               | 0.7872   | 0.8352   |
| 0.4794        | 0.16  | 900  | 0.5008          | 0.8443 | 0.5687               | 0.7893   | 0.8443   |
| 0.5437        | 0.18  | 1000 | 0.4815          | 0.8414 | 0.5610               | 0.7880   | 0.8414   |


### Framework versions

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