readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: rubert-base-cased-token
    results: []
  widget:
    - text: >-
        Однажды я посетил прекрасный городок в горах. На его улицах росли
        удивительные цветы.
      example_title: Example_1
  ---
  
  <!-- 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
  