|
--- |
|
license: cc-by-nc-sa-4.0 |
|
base_model: InstaDeepAI/nucleotide-transformer-v2-100m-multi-species |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: mus_promoter-finetuned-lora-NT-v2-100m-ms |
|
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. --> |
|
|
|
# mus_promoter-finetuned-lora-NT-v2-100m-ms |
|
|
|
This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-v2-100m-multi-species](https://huggingface.co/InstaDeepAI/nucleotide-transformer-v2-100m-multi-species) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0387 |
|
- F1: 0.9867 |
|
- Mcc Score: 0.9683 |
|
- Accuracy: 0.9844 |
|
|
|
## 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 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:| |
|
| 0.4137 | 0.43 | 100 | 0.1128 | 0.9722 | 0.9385 | 0.9688 | |
|
| 0.2366 | 0.85 | 200 | 0.2834 | 0.9459 | 0.8719 | 0.9375 | |
|
| 0.1578 | 1.28 | 300 | 0.1574 | 0.9722 | 0.9385 | 0.9688 | |
|
| 0.0992 | 1.71 | 400 | 0.0585 | 0.9863 | 0.9686 | 0.9844 | |
|
| 0.1293 | 2.14 | 500 | 0.0860 | 0.9863 | 0.9686 | 0.9844 | |
|
| 0.0503 | 2.56 | 600 | 0.0916 | 0.9863 | 0.9686 | 0.9844 | |
|
| 0.0634 | 2.99 | 700 | 0.0265 | 0.9867 | 0.9683 | 0.9844 | |
|
| 0.007 | 3.42 | 800 | 0.0012 | 1.0 | 1.0 | 1.0 | |
|
| 0.0135 | 3.85 | 900 | 0.0015 | 1.0 | 1.0 | 1.0 | |
|
| 0.0113 | 4.27 | 1000 | 0.0387 | 0.9867 | 0.9683 | 0.9844 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.17.1 |
|
- Tokenizers 0.15.2 |
|
|
