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README.md
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---
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license: cc-by-4.0
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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-en-de-finetuned-en-to-de
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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: de-en
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split: validation
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args: de-en
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metrics:
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- name: Bleu
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type: bleu
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value: 30.529
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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-en-de-finetuned-en-to-de
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-de](https://huggingface.co/Helsinki-NLP/opus-mt-en-de) on the wmt16 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2849
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- Bleu: 30.529
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- Rougelsum: 0.5587
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- Gen Len: 27.0521
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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: 5
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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 | Rougelsum | Gen Len |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:-------:|
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| 1.5584 | 1.0 | 12500 | 1.2921 | 30.5519 | 0.5601 | 27.0549 |
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| 1.5649 | 2.0 | 25000 | 1.2877 | 30.578 | 0.5591 | 27.0415 |
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| 1.5686 | 3.0 | 37500 | 1.2859 | 30.5509 | 0.5591 | 27.0401 |
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| 1.5507 | 4.0 | 50000 | 1.2851 | 30.5396 | 0.5589 | 27.0526 |
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| 1.5532 | 5.0 | 62500 | 1.2849 | 30.529 | 0.5587 | 27.0521 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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