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