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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- wmt16
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metrics:
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- bleu
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model-index:
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- name: opus-mt-ru-en-finetuned-ru-to-en
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results:
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- task:
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name: Sequence-to-sequence Language Modeling
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type: text2text-generation
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dataset:
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name: wmt16
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type: wmt16
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args: ru-en
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metrics:
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- name: Bleu
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type: bleu
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value: 30.4049
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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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# opus-mt-ru-en-finetuned-ru-to-en
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ru-en](https://huggingface.co/Helsinki-NLP/opus-mt-ru-en) on the wmt16 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4092
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- Bleu: 30.4049
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- Gen Len: 26.3911
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 1
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- mixed_precision_training: Native AMP
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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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| 2.2606 | 1.0 | 94761 | 1.4092 | 30.4049 | 26.3911 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0.post202
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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