Helsinki-NLP/opus-mt_tiny_eng-deu

OPUS-MT-tiny-fra-eng

Distilled model from a Tatoeba-MT Teacher: OPUS-MT-models/en-de/opus-2020-02-26, which has been trained on the Tatoeba dataset.

We used the OpusDistillery to train new a new student with the tiny architecture, with a regular transformer decoder. For training data, we used Tatoeba. The configuration file fed into OpusDistillery can be found here.

How to run

from transformers import MarianMTModel, MarianTokenizer
model_name = "Helsinki-NLP/opus-mt_tiny_fra-eng"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)
tok = tokenizer("Hello, how are you?", return_tensors="pt").input_ids
output = model.generate(tok)[0]
tokenizer.decode(output, skip_special_tokens=True)

Benchmarks

Teacher

testset	BLEU	chr-F	COMET
Flores+	36.3	63.8	0.8408
Bouquet	37.8	62.1	0.8684

Student

testset	BLEU	chr-F	COMET
Flores+	33.2	61.5	0.8115
Bouquet	31.8	58.2	0.8260