---
library_name: transformers
base_model: sberbank-ai/ruRoberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Administration_RuRoberta_test
  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. -->

# Administration_RuRoberta_test

This model is a fine-tuned version of [sberbank-ai/ruRoberta-large](https://huggingface.co/sberbank-ai/ruRoberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3205
- Accuracy: 0.3316
- Top 2 Accuracy: 0.4452
- Top 3 Accuracy: 0.5217
- Roc Auc: 0.9245
- F1: 0.2788

## 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: 1e-05
- train_batch_size: 12
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Top 2 Accuracy | Top 3 Accuracy | Roc Auc | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|:--------------:|:-------:|:------:|
| 4.9101        | 1.0   | 262  | 4.6292          | 0.0816   | 0.1301         | 0.1773         | 0.7633  | 0.0566 |
| 4.4492        | 2.0   | 524  | 3.8332          | 0.2564   | 0.3737         | 0.4528         | 0.8992  | 0.2009 |
| 3.9241        | 3.0   | 786  | 3.4448          | 0.3163   | 0.4222         | 0.5089         | 0.9194  | 0.2619 |
| 3.0492        | 4.0   | 1048 | 3.3205          | 0.3316   | 0.4452         | 0.5217         | 0.9245  | 0.2788 |


### Framework versions

- Transformers 4.54.1
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4