---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-100m-multi-species
tags:
- generated_from_trainer
metrics:
- f1
- matthews_correlation
- accuracy
model-index:
- name: gut_1024b-finetuned-lora-v2-100m-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-v2-100m-multi-species

This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-100m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-100m-multi-species) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5193
- F1: 0.8251
- Matthews Correlation: 0.5308
- Accuracy: 0.7779
- F1 Score: 0.8251

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:|
| 0.7015        | 0.02  | 100  | 0.6761          | 0.7478 | 0.0                  | 0.5971   | 0.7478   |
| 0.7134        | 0.04  | 200  | 0.6272          | 0.7788 | 0.3129               | 0.6744   | 0.7788   |
| 0.6992        | 0.05  | 300  | 0.5981          | 0.7736 | 0.3943               | 0.7145   | 0.7736   |
| 0.6285        | 0.07  | 400  | 0.6951          | 0.7336 | 0.3658               | 0.6905   | 0.7336   |
| 0.6476        | 0.09  | 500  | 0.6052          | 0.7631 | 0.3673               | 0.7019   | 0.7631   |
| 0.5939        | 0.11  | 600  | 0.5809          | 0.7720 | 0.4050               | 0.7179   | 0.7720   |
| 0.5497        | 0.12  | 700  | 0.5403          | 0.8133 | 0.4867               | 0.7576   | 0.8133   |
| 0.5188        | 0.14  | 800  | 0.5580          | 0.7846 | 0.4694               | 0.7441   | 0.7846   |
| 0.546         | 0.16  | 900  | 0.5767          | 0.8041 | 0.4243               | 0.7154   | 0.8041   |
| 0.5705        | 0.18  | 1000 | 0.5193          | 0.8251 | 0.5308               | 0.7779   | 0.8251   |


### Framework versions

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