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---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-250m-multi-species
tags:
- generated_from_trainer
metrics:
- f1
- matthews_correlation
- accuracy
model-index:
- name: gut_1024b-finetuned-lora-v2-250m-multi-species
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_1024b-finetuned-lora-v2-250m-multi-species
This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-250m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-250m-multi-species) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4815
- F1: 0.8414
- Matthews Correlation: 0.5610
- Accuracy: 0.7880
- F1 Score: 0.8414
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:|
| 0.682 | 0.02 | 100 | 0.5545 | 0.8132 | 0.4597 | 0.7369 | 0.8132 |
| 0.6379 | 0.04 | 200 | 0.6119 | 0.7498 | 0.4244 | 0.7154 | 0.7498 |
| 0.5973 | 0.05 | 300 | 0.5226 | 0.8221 | 0.5154 | 0.7707 | 0.8221 |
| 0.5451 | 0.07 | 400 | 0.5159 | 0.8244 | 0.5010 | 0.7521 | 0.8244 |
| 0.5538 | 0.09 | 500 | 0.5538 | 0.8102 | 0.5043 | 0.7648 | 0.8102 |
| 0.549 | 0.11 | 600 | 0.5220 | 0.8258 | 0.5188 | 0.7715 | 0.8258 |
| 0.4887 | 0.12 | 700 | 0.4940 | 0.8330 | 0.5317 | 0.7728 | 0.8330 |
| 0.4893 | 0.14 | 800 | 0.4951 | 0.8352 | 0.5519 | 0.7872 | 0.8352 |
| 0.4794 | 0.16 | 900 | 0.5008 | 0.8443 | 0.5687 | 0.7893 | 0.8443 |
| 0.5437 | 0.18 | 1000 | 0.4815 | 0.8414 | 0.5610 | 0.7880 | 0.8414 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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