| --- |
| language: |
| - multilingual |
| - pt |
| tags: |
| - bert-large-portuguese-cased |
| - semantic role labeling |
| - finetuned |
| - dependency parsing |
| license: apache-2.0 |
| datasets: |
| - PropBank.Br |
| - CoNLL-2012 |
| - Universal Dependencies |
| metrics: |
| - F1 Measure |
| --- |
| |
| # BERTimbau large fine-tune in Portuguese Universal Dependencies and semantic role labeling |
|
|
| ## Model description |
|
|
| This model is the [`neuralmind/bert-large-portuguese-cased`](https://huggingface.co/neuralmind/bert-large-portuguese-cased) fine-tuned first on the Universal Dependencies Portuguese dataset and then fine-tuned on the PropBank.Br data. This is part of a project from which resulted the following models: |
|
|
| * [liaad/srl-pt_bertimbau-base](https://huggingface.co/liaad/srl-pt_bertimbau-base) |
| * [liaad/srl-pt_bertimbau-large](https://huggingface.co/liaad/srl-pt_bertimbau-large) |
| * [liaad/srl-pt_xlmr-base](https://huggingface.co/liaad/srl-pt_xlmr-base) |
| * [liaad/srl-pt_xlmr-large](https://huggingface.co/liaad/srl-pt_xlmr-large) |
| * [liaad/srl-pt_mbert-base](https://huggingface.co/liaad/srl-pt_mbert-base) |
| * [liaad/srl-en_xlmr-base](https://huggingface.co/liaad/srl-en_xlmr-base) |
| * [liaad/srl-en_xlmr-large](https://huggingface.co/liaad/srl-en_xlmr-large) |
| * [liaad/srl-en_mbert-base](https://huggingface.co/liaad/srl-en_mbert-base) |
| * [liaad/srl-enpt_xlmr-base](https://huggingface.co/liaad/srl-enpt_xlmr-base) |
| * [liaad/srl-enpt_xlmr-large](https://huggingface.co/liaad/srl-enpt_xlmr-large) |
| * [liaad/srl-enpt_mbert-base](https://huggingface.co/liaad/srl-enpt_mbert-base) |
| * [liaad/ud_srl-pt_bertimbau-large](https://huggingface.co/liaad/ud_srl-pt_bertimbau-large) |
| * [liaad/ud_srl-pt_xlmr-large](https://huggingface.co/liaad/ud_srl-pt_xlmr-large) |
| * [liaad/ud_srl-enpt_xlmr-large](https://huggingface.co/liaad/ud_srl-enpt_xlmr-large) |
|
|
| For more information, please see the accompanying article (See BibTeX entry and citation info below) and the [project's github](https://github.com/asofiaoliveira/srl_bert_pt). |
|
|
| ## Intended uses & limitations |
|
|
| #### How to use |
|
|
| To use the transformers portion of this model: |
| ```python |
| from transformers import AutoTokenizer, AutoModel |
| |
| tokenizer = AutoTokenizer.from_pretrained("liaad/ud_srl-pt_bertimbau-large") |
| model = AutoModel.from_pretrained("liaad/ud_srl-pt_bertimbau-large") |
| ``` |
|
|
| To use the full SRL model (transformers portion + a decoding layer), refer to the [project's github](https://github.com/asofiaoliveira/srl_bert_pt). |
|
|
|
|
| #### Limitations and bias |
|
|
| - The model was trained only for 10 epochs in the Universal Dependencies dataset. |
|
|
| ## Training procedure |
|
|
| The model was trained on the Universal Dependencies Portuguese dataset; then on the CoNLL formatted OntoNotes v5.0; then on Portuguese semantic role labeling data (PropBank.Br) using 10-fold Cross-Validation. The 10 resulting models were tested on the folds as well as on a smaller opinion dataset "Buscapé". For more information, please see the accompanying article (See BibTeX entry and citation info below) and the [project's github](https://github.com/asofiaoliveira/srl_bert_pt). |
|
|
| ## Eval results |
|
|
| | Model Name | F<sub>1</sub> CV PropBank.Br (in domain) | F<sub>1</sub> Buscapé (out of domain) | |
| | --------------- | ------ | ----- | |
| | `srl-pt_bertimbau-base` | 76.30 | 73.33 | |
| | `srl-pt_bertimbau-large` | 77.42 | 74.85 | |
| | `srl-pt_xlmr-base` | 75.22 | 72.82 | |
| | `srl-pt_xlmr-large` | 77.59 | 73.84 | |
| | `srl-pt_mbert-base` | 72.76 | 66.89 | |
| | `srl-en_xlmr-base` | 66.59 | 65.24 | |
| | `srl-en_xlmr-large` | 67.60 | 64.94 | |
| | `srl-en_mbert-base` | 63.07 | 58.56 | |
| | `srl-enpt_xlmr-base` | 76.50 | 73.74 | |
| | `srl-enpt_xlmr-large` | **78.22** | 74.55 | |
| | `srl-enpt_mbert-base` | 74.88 | 69.19 | |
| | `ud_srl-pt_bertimbau-large` | 77.53 | 74.49 | |
| | `ud_srl-pt_xlmr-large` | 77.69 | 74.91 | |
| | `ud_srl-enpt_xlmr-large` | 77.97 | **75.05** | |
|
|
|
|
| ### BibTeX entry and citation info |
|
|
| ```bibtex |
| @misc{oliveira2021transformers, |
| title={Transformers and Transfer Learning for Improving Portuguese Semantic Role Labeling}, |
| author={Sofia Oliveira and Daniel Loureiro and Alípio Jorge}, |
| year={2021}, |
| eprint={2101.01213}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL} |
| } |
| ``` |
