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

This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-large-t2t](https://huggingface.co/AIRI-Institute/gena-lm-bert-large-t2t) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1108
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.351         | 0.43  | 100  | 0.2729          | 0.9429 | 0.8814    | 0.9375   |
| 0.1319        | 0.85  | 200  | 0.3380          | 0.9474 | 0.8724    | 0.9375   |
| 0.1245        | 1.28  | 300  | 0.1139          | 0.9737 | 0.9373    | 0.9688   |
| 0.0909        | 1.71  | 400  | 0.2115          | 0.9600 | 0.9039    | 0.9531   |
| 0.0526        | 2.14  | 500  | 0.1748          | 0.9737 | 0.9373    | 0.9688   |
| 0.0355        | 2.56  | 600  | 0.0314          | 0.9867 | 0.9683    | 0.9844   |
| 0.0227        | 2.99  | 700  | 0.0849          | 0.9867 | 0.9683    | 0.9844   |
| 0.0004        | 3.42  | 800  | 0.0131          | 0.9867 | 0.9683    | 0.9844   |
| 0.0075        | 3.85  | 900  | 0.1264          | 0.9867 | 0.9683    | 0.9844   |
| 0.0003        | 4.27  | 1000 | 0.1108          | 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