--- library_name: peft license: mit datasets: - iva_mt_wslot metrics: - bleu model-index: - name: iva_mt_wslot-m2m100_418M-en-pl-lora_adapter results: - task: name: Machine Translation type: text2text-generation dataset: name: iva_mt_wslot type: iva_mt_wslot config: en-pl split: validation args: en-pl metrics: - name: Bleu type: bleu value: 38.2365 language: - pl tags: - machine translation - iva - virtual assistants - natural language understanding - nlu --- # (WIP!) iva_mt_wslot-m2m100_418M-en-pl-lora_adapter Notice: **Although training results are good for some reason inference results are rather poor. I'm leaving this model here as a PoC that PERF LORA adaptation for M2M100 is possible.** This model is a LORA adapted version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the iva_mt_wslot dataset. It achieves the following results on the test set (measured with sacrebleu): - Bleu: 9.33 ## Using The model can be used as follows: First, clone the repository and navigate to the project directory: ```bash git clone https://github.com/cartesinus/multiverb_iva_mt cd multiverb_iva_mt ``` Then: ```python import csv from iva_mt.iva_mt import IVAMT import pandas as pd lang = "es" translator = IVAMT(lang, peft_model_id="cartesinus/iva_mt_wslot-m2m100_418M-en-es-lora_adapter", device="cuda:0", batch_size=128) trans = translator.translate("here your example")[0] ``` ## Training results | Epoch | Training Loss | Validation Loss | Bleu | Gen Len | |:-----:|:-------------:|:---------------:|:-------:|:-------:| | 1 | 7.8621 | 7.6870 | 24.9063 | 19.3322 | | 2 | 7.6340 | 7.5312 | 29.7956 | 19.7533 | | 3 | 7.5582 | 7.4595 | 34.8184 | 20.1269 | | 4 | 7.5047 | 7.4264 | 36.1874 | 20.5621 | | 5 | 7.4888 | 7.4167 | 36.2287 | 20.4417 | | 6 | 7.4560 | 7.4013 | 36.6355 | 20.2241 | | 7 | 7.4477 | 7.3907 | 37.0554 | 20.0945 | | 8 | 7.4422 | 7.3743 | 37.7549 | 20.1589 | | 9 | 7.4311 | 7.3748 | 37.5705 | 19.9370 | | 10 | 7.4294 | 7.3679 | 37.5343 | 20.2241 | | 11 | 7.4114 | 7.3697 | 38.1872 | 20.3836 | | 12 | 7.4224 | 7.3620 | 38.1759 | 20.1785 | | 13 | 7.4334 | 7.3608 | 38.0895 | 20.2996 | | 14 | 7.4133 | 7.3621 | 38.2365 | 20.2948 | | 15 | 7.4158 | 7.3599 | 38.1056 | 20.2010 | ## Framework versions - PEFT 0.5.0