readme: ---
  language:
  - en
  - id
  tags:
  - translation
  license: apache-2.0
  datasets:
  - ALT
  metrics:
  - sacrebleu
  ---
  Pure fine-tuning version of MarianMT en-zh on Indonesian Language
  
  ### Example
  ```
  %%capture
  !pip install transformers transformers[sentencepiece]
  
  from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
  # Download the pretrained model for English-Vietnamese available on the hub
  model = AutoModelForSeq2SeqLM.from_pretrained("CLAck/indo-pure")
  
  tokenizer = AutoTokenizer.from_pretrained("CLAck/indo-pure")
  # Download a tokenizer that can tokenize English since the model Tokenizer doesn't know anymore how to do it
  # We used the one coming from the initial model
  # This tokenizer is used to tokenize the input sentence
  tokenizer_en = AutoTokenizer.from_pretrained('Helsinki-NLP/opus-mt-en-zh')
  # These special tokens are needed to reproduce the original tokenizer
  tokenizer_en.add_tokens(["<2zh>", "<2indo>"], special_tokens=True)
  
  sentence = "The cat is on the table"
  # This token is needed to identify the target language
  input_sentence = "<2indo> " + sentence 
  translated = model.generate(**tokenizer_en(input_sentence, return_tensors="pt", padding=True))
  output_sentence = [tokenizer.decode(t, skip_special_tokens=True) for t in translated]
  ```
  
  ### Training results
  
  | Epoch | Bleu    |
  |:-----:|:-------:|
  | 1.0   | 15.9336 |
  | 2.0   | 28.0175 |
  | 3.0   | 31.6603 |
  | 4.0   | 33.9151 |
  | 5.0   | 35.0472 |
  | 6.0   | 35.8469 |
  | 7.0   | 36.1180 |
  | 8.0   | 36.6018 |
  | 9.0   | 37.1973 |
  | 10.0  | 37.2738 |