---
base_model: AIRI-Institute/gena-lm-bert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results_short_multi
  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. -->

# results_short_multi

This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-base](https://huggingface.co/AIRI-Institute/gena-lm-bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6943
- Accuracy: 0.4984
- F1: 0.6652
- Precision: 0.4984
- Recall: 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6893        | 1.0   | 3125 | 0.6936          | 0.5025   | 0.6689 | 0.5025    | 1.0    |
| 0.7022        | 2.0   | 6250 | 0.6948          | 0.5025   | 0.6689 | 0.5025    | 1.0    |
| 0.6899        | 3.0   | 9375 | 0.6940          | 0.5025   | 0.6689 | 0.5025    | 1.0    |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1