---
language:
- de
- en
datasets:
- wmt14
pipeline_tag: translation
model-index:
- name: leukas/mt5-large-wmt14-deen
  results:
  - task:
      type: translation
      name: Translation
    dataset:
      name: wmt14
      type: wmt14
      config: de-en
      split: test
    metrics:
    - type: bleu
      value: 15.9193
      name: BLEU
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTc4MzAyMmM0MzhhOWRkMjdhNjNlYjM2NzYzY2RhN2ZlZTZlMjc2ZTU2NDNiMDViMzBiNGJkZjZkNDVjOGQzMyIsInZlcnNpb24iOjF9.peedpgE2-qr9AnNNkPfS-k3Dym9n84X3IGTYYUlrrdLtGwh1eJa7R5RLoWujQXb8rlGZV25BaIrH5vLtLX20BA
    - type: loss
      value: 1.0981481075286865
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzRhMGVlYTc5ZWU5ODE4MjczYjI3ZmQ3NzVmMWE5NzhmNjUzNjcyNTcxMmE5YjgwMmMwZWJmYzU4ZTIwNWEyZCIsInZlcnNpb24iOjF9.hgJ8jVwR9Et143miqygebY82ui8yUoFAoGj8xAdu3x9H5KUxh-i2rHNYFGV1Ln5Nf6N8oQdKMEUpLP6jYKhQDA
    - type: gen_len
      value: 19.0869
      name: gen_len
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjIzOGVkMDM3MjU1NjQ4YTYxNzI0OTY3ZDcwM2I2ZWI2YWY4NTQ5YjA3NzIwNTIzNDViNTQxMWJhZGQ5ZjBmNiIsInZlcnNpb24iOjF9.X56ymiUiJQQr8J-h67i8qL3D8_63JqChAwbdiZtGpB2xpst0uacEPl0cmDABDaf78ilQVASFZYkwoG9SnkEhAg
---

# mt5-large-wmt14-deen

This model is released as part of the work from [Are Character-level Translations Worth the Wait? Comparing Character- and Subword-level Models for Machine Translation](https://arxiv.org/abs/2302.14220).
It is an mT5 model finetuned on German-->English translation the WMT14 dataset. 

To use the model correctly, you must prepend the prompt with "translate X to Y: ", where X and Y are your source and target languages (e.g. German, English).


NOTE: The decoder_start_token_id is 259 for byt5 models and 250099 for mt5 models, which is different from the default token from google's byt5 and mt5 models (which is 0).