---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-500m-1000g
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: mus_promoter-finetuned-lora-NT-500m-1000g
  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. -->

# mus_promoter-finetuned-lora-NT-500m-1000g

This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-500m-1000g](https://huggingface.co/InstaDeepAI/nucleotide-transformer-500m-1000g) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3065
- F1: 0.9351
- Mcc Score: 0.8414
- Accuracy: 0.9219

## 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     | Mcc Score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.6126        | 0.43  | 100  | 0.4697          | 0.8767 | 0.7135    | 0.8594   |
| 0.3854        | 0.85  | 200  | 0.2682          | 0.9296 | 0.8460    | 0.9219   |
| 0.4832        | 1.28  | 300  | 0.2444          | 0.9296 | 0.8460    | 0.9219   |
| 0.3536        | 1.71  | 400  | 0.3433          | 0.9167 | 0.8113    | 0.9062   |
| 0.3215        | 2.14  | 500  | 0.3475          | 0.9351 | 0.8414    | 0.9219   |
| 0.2961        | 2.56  | 600  | 0.2347          | 0.9231 | 0.8108    | 0.9062   |
| 0.2742        | 2.99  | 700  | 0.3438          | 0.9333 | 0.8395    | 0.9219   |
| 0.2375        | 3.42  | 800  | 0.3448          | 0.9351 | 0.8414    | 0.9219   |
| 0.2438        | 3.85  | 900  | 0.2789          | 0.9351 | 0.8414    | 0.9219   |
| 0.2104        | 4.27  | 1000 | 0.3065          | 0.9351 | 0.8414    | 0.9219   |


### Framework versions

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