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---
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 |