---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-2.5b-multi-species
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
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-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-2.5b-multi-species) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6652
- F1: 0.8473
- Mcc Score: 0.5631
- Accuracy: 0.7930

## 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: 3
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 1.4035        | 0.05  | 100  | 0.6460          | 0.7279 | 0.3679    | 0.6875   |
| 1.0673        | 0.11  | 200  | 0.4946          | 0.8437 | 0.5583    | 0.7930   |
| 0.7808        | 0.16  | 300  | 0.6190          | 0.7766 | 0.2749    | 0.6719   |
| 0.8938        | 0.21  | 400  | 2.1858          | 0.0    | 0.0       | 0.3906   |
| 0.9329        | 0.26  | 500  | 0.8452          | 0.8352 | 0.5179    | 0.7656   |
| 0.8721        | 0.32  | 600  | 0.7470          | 0.5286 | 0.2993    | 0.5820   |
| 0.6548        | 0.37  | 700  | 0.6967          | 0.8242 | 0.4769    | 0.75     |
| 0.6719        | 0.42  | 800  | 0.9450          | 0.7913 | 0.4425    | 0.7383   |
| 0.8265        | 0.47  | 900  | 0.5426          | 0.8328 | 0.5234    | 0.7773   |
| 0.5561        | 0.53  | 1000 | 0.6652          | 0.8473 | 0.5631    | 0.7930   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2