---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-500m-1000g
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: gut_1024-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. -->

# gut_1024-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: 0.4974
- F1: 0.8222
- Mcc Score: 0.5121

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|
| 0.81          | 0.02  | 100  | 0.6937          | 0.7478 | 0.0       |
| 0.7437        | 0.04  | 200  | 0.9181          | 0.0    | 0.0       |
| 0.7256        | 0.05  | 300  | 0.6935          | 0.7478 | 0.0       |
| 0.6717        | 0.07  | 400  | 0.6097          | 0.7208 | 0.3287    |
| 0.6583        | 0.09  | 500  | 0.6723          | 0.6032 | 0.3371    |
| 0.6158        | 0.11  | 600  | 0.5444          | 0.7973 | 0.4579    |
| 0.5618        | 0.12  | 700  | 0.5551          | 0.7728 | 0.4420    |
| 0.5324        | 0.14  | 800  | 0.5200          | 0.7764 | 0.4601    |
| 0.5326        | 0.16  | 900  | 0.5166          | 0.8190 | 0.4874    |
| 0.5769        | 0.18  | 1000 | 0.4974          | 0.8222 | 0.5121    |


### Framework versions

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