| language: | |
| - en | |
| - vi | |
| - multilingual | |
| license: apache-2.0 | |
| tags: | |
| - translation | |
| datasets: | |
| - ALT | |
| metrics: | |
| - sacrebleu | |
| This is a finetuning of a MarianMT pretrained on Chinese-English. The target language pair is Vietnamese-English. | |
| ### 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/vi-en") | |
| tokenizer = AutoTokenizer.from_pretrained("CLAck/vi-en") | |
| sentence = your_vietnamese_sentence | |
| # This token is needed to identify the source language | |
| input_sentence = "<2vi> " + sentence | |
| translated = model.generate(**tokenizer(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 | 21.3180 | | |
| | 2.0 | 26.8012 | | |
| | 3.0 | 29.3578 | | |
| | 4.0 | 31.5178 | | |
| | 5.0 | 32.8740 | | |