|
--- |
|
license: cc-by-nc-sa-4.0 |
|
base_model: InstaDeepAI/nucleotide-transformer-2.5b-1000g |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
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-2.5b-1000g](https://huggingface.co./InstaDeepAI/nucleotide-transformer-2.5b-1000g) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1687 |
|
- F1: 0.9863 |
|
- Mcc Score: 0.9686 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:| |
|
| 0.2508 | 0.43 | 100 | 0.1791 | 0.9863 | 0.9686 | |
|
| 0.0793 | 0.85 | 200 | 0.4908 | 0.9429 | 0.8814 | |
|
| 0.0408 | 1.28 | 300 | 0.3990 | 0.9600 | 0.9039 | |
|
| 0.0184 | 1.71 | 400 | 0.2259 | 0.9730 | 0.9359 | |
|
| 0.014 | 2.14 | 500 | 0.1308 | 0.9863 | 0.9686 | |
|
| 0.0313 | 2.56 | 600 | 0.1841 | 0.9863 | 0.9686 | |
|
| 0.0162 | 2.99 | 700 | 0.4267 | 0.9730 | 0.9359 | |
|
| 0.0114 | 3.42 | 800 | 0.2700 | 0.9730 | 0.9359 | |
|
| 0.0 | 3.85 | 900 | 0.1612 | 0.9863 | 0.9686 | |
|
| 0.0 | 4.27 | 1000 | 0.1687 | 0.9863 | 0.9686 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.1 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.17.1 |
|
- Tokenizers 0.15.2 |
|
|
