---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-500m-human-ref
tags:
- generated_from_trainer
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-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: 0.2358
- F1 Score: 0.9363

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1 Score |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6471        | 0.0158 | 100  | 0.3372          | 0.8961   |
| 0.3843        | 0.0316 | 200  | 0.2311          | 0.9029   |
| 0.3449        | 0.0474 | 300  | 0.2503          | 0.9145   |
| 0.3466        | 0.0632 | 400  | 0.2059          | 0.9211   |
| 0.2615        | 0.0790 | 500  | 0.2347          | 0.9281   |
| 0.295         | 0.0948 | 600  | 0.2221          | 0.9199   |
| 0.272         | 0.1107 | 700  | 0.2228          | 0.9303   |
| 0.2507        | 0.1265 | 800  | 0.2339          | 0.9226   |
| 0.2356        | 0.1423 | 900  | 0.2088          | 0.9388   |
| 0.1854        | 0.1581 | 1000 | 0.2358          | 0.9363   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0