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---
license: mit
language:
- ru
- kbd
datasets:
- anzorq/kbd-ru
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.
tags:
- translation
---
<!-- 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 |