---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-500m-human-ref
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: gut_1024-finetuned-lora-NT-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. -->

# gut_1024-finetuned-lora-NT-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: 0.5875
- F1: 0.7769
- Mcc Score: 0.3628

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|
| 0.8285        | 0.02  | 100  | 0.6805          | 0.7478 | 0.0       |
| 0.7353        | 0.04  | 200  | 0.6825          | 0.7478 | 0.0       |
| 0.7131        | 0.05  | 300  | 0.6285          | 0.7644 | 0.2641    |
| 0.7292        | 0.07  | 400  | 0.6473          | 0.7680 | 0.3281    |
| 0.6666        | 0.09  | 500  | 0.6445          | 0.7199 | 0.3140    |
| 0.6413        | 0.11  | 600  | 0.6176          | 0.7702 | 0.3201    |
| 0.6056        | 0.12  | 700  | 0.6388          | 0.7170 | 0.3337    |
| 0.6215        | 0.14  | 800  | 0.6161          | 0.7506 | 0.3337    |
| 0.596         | 0.16  | 900  | 0.6000          | 0.7814 | 0.3515    |
| 0.6444        | 0.18  | 1000 | 0.5875          | 0.7769 | 0.3628    |


### Framework versions

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