---
base_model: AIRI-Institute/gena-lm-bert-base-t2t-multi
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: gut_1024-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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# gut_1024-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: 0.4764
- F1: 0.8478
- Mcc Score: 0.5903
- Accuracy: 0.8049

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.7012        | 0.02  | 100  | 0.6683          | 0.7478 | 0.0       | 0.5971   |
| 0.7003        | 0.04  | 200  | 0.6391          | 0.7825 | 0.3306    | 0.6710   |
| 0.6583        | 0.05  | 300  | 0.6211          | 0.7853 | 0.3430    | 0.6778   |
| 0.6381        | 0.07  | 400  | 0.6512          | 0.7812 | 0.3247    | 0.6681   |
| 0.6438        | 0.09  | 500  | 0.6524          | 0.3380 | 0.1874    | 0.5004   |
| 0.6028        | 0.11  | 600  | 0.5646          | 0.8004 | 0.5013    | 0.7606   |
| 0.5154        | 0.12  | 700  | 0.5437          | 0.8392 | 0.5576    | 0.7884   |
| 0.5226        | 0.14  | 800  | 0.4823          | 0.8503 | 0.5901    | 0.8024   |
| 0.5104        | 0.16  | 900  | 0.4856          | 0.8452 | 0.5851    | 0.8028   |
| 0.5538        | 0.18  | 1000 | 0.4764          | 0.8478 | 0.5903    | 0.8049   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2