
# roberta-large-wechsel-ukrainian

[`roberta-base`](https://huggingface.co/roberta-base) transferred to Ukrainian using the method from the NAACL2022 paper [WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models](https://aclanthology.org/2022.naacl-main.293/).

# Evaluation

Evaluation was done on [lang-uk's ner-uk project](https://github.com/lang-uk/ner-uk), the Ukrainian portion of [WikiANN](https://huggingface.co/datasets/wikiann) and the [Ukrainian IU corpus from the Universal Dependencies project](https://github.com/UniversalDependencies/UD_Ukrainian-IU). Evaluation results are the mean of 5 runs with different seeds.

__Validation Results__

|                                                  | lang-uk NER (Micro F1)   | WikiANN (Micro F1)     | UD Ukrainian IU POS (Accuracy)   |
|:-------------------------------------------------|:-------------------------|:-------------|:-------------------------|
| roberta-base-wechsel-ukrainian                   | 88.06 (0.50)             | 92.96 (0.08) | 98.70 (0.05)             |
| roberta-large-wechsel-ukrainian                  | __89.27 (0.53)__             | __93.22 (0.15)__ | __98.86 (0.03)__             |
|
| roberta-base-scratch-ukrainian*                  | 85.49 (0.88)             | 91.91 (0.08) | 98.49 (0.04)             |
| roberta-large-scratch-ukrainian*                 | 86.54 (0.70)             | 92.39 (0.16) | 98.65 (0.09)             |
|
| dbmdz/electra-base-ukrainian-cased-discriminator | 87.49 (0.52)             | 93.20 (0.16) | 98.60 (0.03)             |
| xlm-roberta-base                                 | 86.68 (0.44)             | 92.41 (0.13) | 98.53 (0.02)             |
| xlm-roberta-large                                | 86.64 (1.61)             | 93.01 (0.13) | 98.71 (0.04)             |

__Test Results__

|                                                  | lang-uk NER (Micro F1)   | WikiANN (Micro F1)     | UD Ukrainian IU POS (Accuracy)   |
|:-------------------------------------------------|:-------------------------|:-------------|:-------------------------|
| roberta-base-wechsel-ukrainian                   | 90.81 (1.51)             | 92.98 (0.12) | 98.57 (0.03)             |
| roberta-large-wechsel-ukrainian                  | __91.24 (1.16)__             | __93.22 (0.17)__ | __98.74 (0.06)__             |
|
| roberta-base-scratch-ukrainian*                  | 89.57 (1.01)             | 92.05 (0.09) | 98.31 (0.08)             |
| roberta-large-scratch-ukrainian*                 | 89.96 (0.89)             | 92.49 (0.15) | 98.52 (0.04)             |
|
| dbmdz/electra-base-ukrainian-cased-discriminator | 90.43 (1.29)             | 92.99 (0.11) | 98.59 (0.06)             |
| xlm-roberta-base                                 | 90.86 (0.81)             | 92.27 (0.09) | 98.45 (0.07)             |
| xlm-roberta-large                                | 90.16 (2.98)             | 92.92 (0.19) | 98.71 (0.04)             |

\*trained using the same exact training setup as the wechsel-\* models, but without parameter transfer from WECHSEL.


# License

MIT
{"language": "uk", "license": "mit"}
transformers pytorch safetensors roberta fill-mask uk license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #roberta #fill-mask #uk #license-mit #autotrain_compatible #endpoints_compatible #region-us 

roberta-large-wechsel-ukrainian
===============================


'roberta-base' transferred to Ukrainian using the method from the NAACL2022 paper WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.


Evaluation
==========


Evaluation was done on lang-uk's ner-uk project, the Ukrainian portion of WikiANN and the Ukrainian IU corpus from the Universal Dependencies project. Evaluation results are the mean of 5 runs with different seeds.


**Validation Results**



**Test Results**



\*trained using the same exact training setup as the wechsel-\* models, but without parameter transfer from WECHSEL.


License
=======


MIT



TAGS
#transformers #pytorch #safetensors #roberta #fill-mask #uk #license-mit #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #safetensors #roberta #fill-mask #uk #license-mit #autotrain_compatible #endpoints_compatible #region-us 
