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

This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-base-t2t-multi](https://huggingface.co/AIRI-Institute/gena-lm-bert-base-t2t-multi) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0021
- F1: 1.0
- Mcc Score: 1.0
- Accuracy: 1.0

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.169         | 0.43  | 100  | 0.2552          | 0.9429 | 0.8814    | 0.9375   |
| 0.1379        | 0.85  | 200  | 0.2600          | 0.9600 | 0.9039    | 0.9531   |
| 0.0749        | 1.28  | 300  | 0.1726          | 0.9737 | 0.9373    | 0.9688   |
| 0.0708        | 1.71  | 400  | 0.0171          | 0.9863 | 0.9686    | 0.9844   |
| 0.0579        | 2.14  | 500  | 0.1011          | 0.9863 | 0.9686    | 0.9844   |
| 0.0512        | 2.56  | 600  | 0.0993          | 0.9722 | 0.9385    | 0.9688   |
| 0.0238        | 2.99  | 700  | 0.0065          | 1.0    | 1.0       | 1.0      |
| 0.0108        | 3.42  | 800  | 0.0605          | 0.9863 | 0.9686    | 0.9844   |
| 0.024         | 3.85  | 900  | 0.0029          | 1.0    | 1.0       | 1.0      |
| 0.0178        | 4.27  | 1000 | 0.0021          | 1.0    | 1.0       | 1.0      |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2