---
library_name: transformers
license: apache-2.0
base_model: ai-forever/ruBert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: mmodel_v2
  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. -->

# mmodel_v2

This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggingface.co/ai-forever/ruBert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0613
- Accuracy: 0.7115
- F1: 0.7076

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.631         | 1.0   | 693  | 1.2443          | 0.6671   | 0.6599 |
| 1.1397        | 2.0   | 1386 | 1.0194          | 0.7142   | 0.7069 |
| 0.8178        | 3.0   | 2079 | 0.9897          | 0.7126   | 0.7057 |
| 0.667         | 4.0   | 2772 | 1.0223          | 0.7099   | 0.7049 |
| 0.5712        | 5.0   | 3465 | 1.0613          | 0.7115   | 0.7076 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3