---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-500m-human-ref
tags:
- generated_from_trainer
metrics:
- f1
- matthews_correlation
- accuracy
model-index:
- name: mus_promoter-finetuned-lora-500m-human-ref
  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-500m-human-ref

This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-500m-human-ref](https://huggingface.co/InstaDeepAI/nucleotide-transformer-500m-human-ref) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4605
- F1: 0.9444
- Matthews Correlation: 0.8749
- Accuracy: 0.9375
- F1 Score: 0.9444

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:|
| 0.7975        | 0.43  | 100  | 0.3190          | 0.9231 | 0.8108               | 0.9062   | 0.9231   |
| 0.3818        | 0.85  | 200  | 0.2951          | 0.9167 | 0.8113               | 0.9062   | 0.9167   |
| 0.3829        | 1.28  | 300  | 0.5043          | 0.9    | 0.7507               | 0.875    | 0.9      |
| 0.2565        | 1.71  | 400  | 0.2655          | 0.9351 | 0.8414               | 0.9219   | 0.9351   |
| 0.2098        | 2.14  | 500  | 0.3518          | 0.9333 | 0.8395               | 0.9219   | 0.9333   |
| 0.1841        | 2.56  | 600  | 0.2601          | 0.9211 | 0.8076               | 0.9062   | 0.9211   |
| 0.0804        | 2.99  | 700  | 0.3953          | 0.9315 | 0.8411               | 0.9219   | 0.9315   |
| 0.0463        | 3.42  | 800  | 0.4732          | 0.9444 | 0.8749               | 0.9375   | 0.9444   |
| 0.057         | 3.85  | 900  | 0.4799          | 0.9444 | 0.8749               | 0.9375   | 0.9444   |
| 0.0144        | 4.27  | 1000 | 0.4605          | 0.9444 | 0.8749               | 0.9375   | 0.9444   |


### Framework versions

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