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---
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-50m-multi-species
tags:
- generated_from_trainer
metrics:
- f1
- matthews_correlation
- accuracy
model-index:
- name: gut_1024b-finetuned-lora-v2-50m-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-v2-50m-multi-species
This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-50m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-50m-multi-species) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4237
- F1: 0.8660
- Matthews Correlation: 0.6384
- Accuracy: 0.8252
- F1 Score: 0.8660
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------:|:--------:|:--------:|
| 0.6937 | 0.02 | 100 | 0.6419 | 0.7758 | 0.2955 | 0.6584 | 0.7758 |
| 0.652 | 0.04 | 200 | 0.5536 | 0.8102 | 0.4925 | 0.7601 | 0.8102 |
| 0.5786 | 0.05 | 300 | 0.5052 | 0.8286 | 0.5183 | 0.7682 | 0.8286 |
| 0.5083 | 0.07 | 400 | 0.5294 | 0.8230 | 0.4972 | 0.7475 | 0.8230 |
| 0.5439 | 0.09 | 500 | 0.4759 | 0.8484 | 0.5865 | 0.8019 | 0.8484 |
| 0.4945 | 0.11 | 600 | 0.5015 | 0.8363 | 0.5424 | 0.7770 | 0.8363 |
| 0.4564 | 0.12 | 700 | 0.4767 | 0.8448 | 0.5911 | 0.8057 | 0.8448 |
| 0.4306 | 0.14 | 800 | 0.4619 | 0.8517 | 0.6066 | 0.8129 | 0.8517 |
| 0.4588 | 0.16 | 900 | 0.4485 | 0.8532 | 0.5973 | 0.8003 | 0.8532 |
| 0.4784 | 0.18 | 1000 | 0.4237 | 0.8660 | 0.6384 | 0.8252 | 0.8660 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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