---
base_model: AIRI-Institute/gena-lm-bert-base-lastln-t2t
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: mus_promoter-finetuned-lora-bert-base-lastln-t2t
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mus_promoter-finetuned-lora-bert-base-lastln-t2t

This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-base-lastln-t2t](https://huggingface.co/AIRI-Institute/gena-lm-bert-base-lastln-t2t) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0934
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.3791        | 0.43  | 100  | 0.2575          | 0.9296 | 0.8460    | 0.9219   |
| 0.1329        | 0.85  | 200  | 0.0857          | 0.9730 | 0.9359    | 0.9688   |
| 0.1085        | 1.28  | 300  | 0.1337          | 0.9730 | 0.9359    | 0.9688   |
| 0.0609        | 1.71  | 400  | 0.1476          | 0.9730 | 0.9359    | 0.9688   |
| 0.041         | 2.14  | 500  | 0.0040          | 1.0    | 1.0       | 1.0      |
| 0.0165        | 2.56  | 600  | 0.0766          | 0.9863 | 0.9686    | 0.9844   |
| 0.0152        | 2.99  | 700  | 0.0908          | 0.9867 | 0.9683    | 0.9844   |
| 0.0087        | 3.42  | 800  | 0.0940          | 0.9730 | 0.9359    | 0.9688   |
| 0.0156        | 3.85  | 900  | 0.0911          | 0.9867 | 0.9683    | 0.9844   |
| 0.0081        | 4.27  | 1000 | 0.0934          | 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