---
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_1024-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_1024-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: 0.4480
- F1: 0.8532
- Matthews Correlation: 0.6018
- Accuracy: 0.8091
- F1 Score: 0.8532

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:|
| 0.7913        | 0.02  | 100  | 0.6865          | 0.7478 | 0.0                  | 0.5971   | 0.7478   |
| 0.6762        | 0.04  | 200  | 0.7888          | 0.6217 | 0.3157               | 0.6284   | 0.6217   |
| 0.6291        | 0.05  | 300  | 0.5765          | 0.7628 | 0.4323               | 0.7234   | 0.7628   |
| 0.563         | 0.07  | 400  | 0.5184          | 0.8304 | 0.5258               | 0.7724   | 0.8304   |
| 0.5206        | 0.09  | 500  | 0.5402          | 0.8281 | 0.5142               | 0.7580   | 0.8281   |
| 0.4639        | 0.11  | 600  | 0.4681          | 0.8461 | 0.5775               | 0.7969   | 0.8461   |
| 0.4359        | 0.12  | 700  | 0.5136          | 0.8470 | 0.5774               | 0.7918   | 0.8470   |
| 0.4861        | 0.14  | 800  | 0.4530          | 0.8365 | 0.5714               | 0.7965   | 0.8365   |
| 0.4923        | 0.16  | 900  | 0.4480          | 0.8496 | 0.5889               | 0.8024   | 0.8496   |
| 0.4369        | 0.18  | 1000 | 0.4480          | 0.8532 | 0.6018               | 0.8091   | 0.8532   |


### Framework versions

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