---
language:
- ru
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
widget:
- text: Однажды я посетил прекрасный городок в горах. На его улицах росли удивительные
    цветы.
  example_title: Example_1
pipeline_tag: token-classification
base_model: DeepPavlov/rubert-base-cased
model-index:
- name: rubert-base-cased-token
  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. -->

# rubert-base-cased-token

This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the OpenCorpora dataset [opencorpora.org](http://opencorpora.org/).
It achieves the following results on the evaluation set:
- Loss: 0.2595
- Precision: 0.9304
- Recall: 0.9334
- F1: 0.9319
- Accuracy: 0.9424

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

Tokens classification from OpenCorpora: [opencorpora.org](http://opencorpora.org/dict.php?act=gram)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 69   | 0.6926          | 0.7731    | 0.7674 | 0.7702 | 0.8200   |
| No log        | 2.0   | 138  | 0.3744          | 0.8665    | 0.8807 | 0.8735 | 0.9003   |
| No log        | 3.0   | 207  | 0.2891          | 0.9004    | 0.9071 | 0.9037 | 0.9231   |
| No log        | 4.0   | 276  | 0.2566          | 0.9123    | 0.9217 | 0.9170 | 0.9327   |
| No log        | 5.0   | 345  | 0.2587          | 0.9211    | 0.9255 | 0.9233 | 0.9366   |
| No log        | 6.0   | 414  | 0.2472          | 0.9264    | 0.9289 | 0.9276 | 0.9401   |
| No log        | 7.0   | 483  | 0.2589          | 0.9267    | 0.9313 | 0.9290 | 0.9406   |
| 0.3825        | 8.0   | 552  | 0.2559          | 0.9286    | 0.9334 | 0.9310 | 0.9416   |
| 0.3825        | 9.0   | 621  | 0.2578          | 0.9304    | 0.9339 | 0.9321 | 0.9425   |
| 0.3825        | 10.0  | 690  | 0.2595          | 0.9304    | 0.9334 | 0.9319 | 0.9424   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2