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README.md
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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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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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---
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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 an unknown dataset.
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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
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