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README.md
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---
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license: mit
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base_model:
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tags:
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- translation
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- generated_from_trainer
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datasets:
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- wmt16
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model-index:
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- name: m2m100_418M
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results:
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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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# m2m100_418M
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This model is a fine-tuned version of [
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## Model description
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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:
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 10
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- total_train_batch_size:
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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:
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### Framework versions
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---
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license: mit
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base_model: kazandaev/m2m100_418M
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tags:
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- translation
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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: m2m100_418M
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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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config: ru-en
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split: validation
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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: 32.0585
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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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# m2m100_418M
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This model is a fine-tuned version of [kazandaev/m2m100_418M](https://huggingface.co/kazandaev/m2m100_418M) on the wmt16 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8954
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- Bleu: 32.0585
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- Gen Len: 36.1643
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## Model description
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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: 4
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 10
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- total_train_batch_size: 40
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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: 2
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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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| 0.8087 | 1.0 | 47790 | 0.9542 | 30.786 | 36.1469 |
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| 0.7266 | 2.0 | 95580 | 0.8954 | 32.0585 | 36.1643 |
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### Framework versions
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