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--- |
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license: mit |
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language: |
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- ru |
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- kbd |
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widget: |
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- text: "Я иду домой." |
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example_title: "Я иду домой." |
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- text: "Дети играют во дворе." |
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example_title: "Дети играют во дворе." |
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- text: "Сколько тебе лет?" |
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example_title: "Сколько тебе лет?" |
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- text: "На следующий день мы отправились в путь." |
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example_title: "На следующий день мы отправились в путь." |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# m2m100_ru_kbd_44K |
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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.. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9399 |
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- Bleu: 22.389 |
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- Gen Len: 16.562 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
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| 2.2391 | 0.18 | 1000 | 1.9921 | 7.4066 | 16.377 | |
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| 1.8436 | 0.36 | 2000 | 1.6756 | 9.3443 | 18.428 | |
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| 1.63 | 0.53 | 3000 | 1.5361 | 10.9057 | 17.134 | |
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| 1.5205 | 0.71 | 4000 | 1.3994 | 12.6061 | 17.471 | |
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| 1.4471 | 0.89 | 5000 | 1.3107 | 14.4452 | 16.985 | |
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| 1.1915 | 1.07 | 6000 | 1.2462 | 15.1903 | 16.544 | |
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| 1.1165 | 1.25 | 7000 | 1.1917 | 16.3859 | 17.044 | |
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| 1.0654 | 1.43 | 8000 | 1.1351 | 17.617 | 16.481 | |
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| 1.0464 | 1.6 | 9000 | 1.0939 | 18.649 | 16.517 | |
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| 1.0376 | 1.78 | 10000 | 1.0603 | 18.2567 | 17.152 | |
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| 1.0027 | 1.96 | 11000 | 1.0184 | 20.6011 | 16.875 | |
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| 0.7741 | 2.14 | 12000 | 1.0159 | 20.4801 | 16.488 | |
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| 0.7566 | 2.32 | 13000 | 0.9899 | 21.6967 | 16.681 | |
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| 0.7346 | 2.49 | 14000 | 0.9738 | 21.8249 | 16.679 | |
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| 0.7397 | 2.67 | 15000 | 0.9555 | 21.569 | 16.608 | |
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| 0.6919 | 2.85 | 16000 | 0.9441 | 22.4658 | 16.493 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
