readme: ---
  license: mit
  
  language:
  - ru
  - kbd
  
  widget:
  - text: "Я иду домой."
    example_title: "Я иду домой."
  - text: "Дети играют во дворе."
    example_title: "Дети играют во дворе."
  - text: "Сколько тебе лет?"
    example_title: "Сколько тебе лет?"
  - text: "На следующий день мы отправились в путь."
    example_title: "На следующий день мы отправились в путь."
  ---
  
  <!-- 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. -->
  
  # m2m100_ru_kbd_44K
  
  This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on a ru-kbd dataset, containing 44K sentences from books, textbooks, dictionaries etc..
  It achieves the following results on the evaluation set:
  - Loss: 0.9399
  - Bleu: 22.389
  - Gen Len: 16.562
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 2.2391        | 0.18  | 1000  | 1.9921          | 7.4066  | 16.377  |
  | 1.8436        | 0.36  | 2000  | 1.6756          | 9.3443  | 18.428  |
  | 1.63          | 0.53  | 3000  | 1.5361          | 10.9057 | 17.134  |
  | 1.5205        | 0.71  | 4000  | 1.3994          | 12.6061 | 17.471  |
  | 1.4471        | 0.89  | 5000  | 1.3107          | 14.4452 | 16.985  |
  | 1.1915        | 1.07  | 6000  | 1.2462          | 15.1903 | 16.544  |
  | 1.1165        | 1.25  | 7000  | 1.1917          | 16.3859 | 17.044  |
  | 1.0654        | 1.43  | 8000  | 1.1351          | 17.617  | 16.481  |
  | 1.0464        | 1.6   | 9000  | 1.0939          | 18.649  | 16.517  |
  | 1.0376        | 1.78  | 10000 | 1.0603          | 18.2567 | 17.152  |
  | 1.0027        | 1.96  | 11000 | 1.0184          | 20.6011 | 16.875  |
  | 0.7741        | 2.14  | 12000 | 1.0159          | 20.4801 | 16.488  |
  | 0.7566        | 2.32  | 13000 | 0.9899          | 21.6967 | 16.681  |
  | 0.7346        | 2.49  | 14000 | 0.9738          | 21.8249 | 16.679  |
  | 0.7397        | 2.67  | 15000 | 0.9555          | 21.569  | 16.608  |
  | 0.6919        | 2.85  | 16000 | 0.9441          | 22.4658 | 16.493  |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.10.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1