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README.md
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license: apache-2.0
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---
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---
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license: apache-2.0
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language:
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- sr
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metrics:
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- accuracy
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- wer
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library_name: transformers
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tags:
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- legal
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---
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# BERTić-COMtext-SR-legal-MSD-ijekavica
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**BERTić-COMtext-SR-legal-MSD-ijekavica** is a variant of the [BERTić](https://huggingface.co/classla/bcms-bertic) model, fine-tuned on the task of morphosyntactic (MSD) tag prediction in Serbian legal texts written in the Ijekavian pronunciation.
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The model was fine-tuned for 15 epochs on the Ijekavian variant of the [COMtext.SR.legal](https://github.com/ICEF-NLP/COMtext.SR) dataset.
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# Benchmarking
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This model was evaluated on the tasks of MSD prediction and lemmatization of Serbian legal texts.
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Lemmatization was performed using the predicted MSD tags and the [hrLex](http://hdl.handle.net/11356/1232) inflectional lexicon.
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Accuracy and Word Error Rate were used as evaluation metrics.
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This model was compared to:
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- The [CLASSLA](http://pypi.org/project/classla/) library
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- A variant of [BERTić](https://huggingface.co/classla/bcms-bertic) fine-tuned for MSD prediction using the [SETimes.SR 2.0](http://hdl.handle.net/11356/1843) corpus of newswire texts
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- [SrBERTa](http://huggingface.co/nemanjaPetrovic/SrBERTa), a model specially trained on Serbian legal texts
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All large language models were fine-tuned for 15 epochs.
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CLASSLA and BERTić-SETimes were directly tested on the entire COMtext.SR.legal.ijekavica corpus.
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BERTić-COMtext-SR-legal-MSD-ijekavica and SrBERTa were fine-tuned and evaluated on the COMtext.SR.legal.ijekavica corpus using 10-fold CV.
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The code and data to run these experiments is available on the [COMtext.SR GitHub repository](https://github.com/ICEF-NLP/COMtext.SR).
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## Results
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| Model | MSD ACC | MSD WER | Lemma ACC | Lemma WER |
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| ----------------------------------------------------------- | -------- | ---------- | --------- | ---------- |
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| CLASSLA-SR (gold tokens) | 0.9150 | 0.0850 | 0.9036 | 0.0964 |
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| *CLASSLA-SR (CLASSLA tokenizer)* | / | *0.0977* | / | *0.1135* |
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| CLASSLA-HR (gold tokens) | 0.9062 | 0.0938 | 0.9353 | 0.0647 |
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| *CLASSLA-HR (CLASSLA tokenizer)* | / | *0.1076* | / | *0.0827* |
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| BERTić-SETimes.SR (gold tokens) | 0.9234 | 0.0766 | 0.9412 | 0.0588 |
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| *BERTić-SETimes.SR (CLASSLA tokenizer)* | / | *0.0883* | / | *0.0780* |
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| BERTić-COMtext-SR-legal-MSD-ijekavica (gold tokens) |**0.9674**| **0.0326** |**0.9429** | **0.0571** |
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| *BERTić-COMtext-SR-legal-MSD-ijekavica (CLASSLA tokenizer)* | / |***0.0447***| / |***0.0763***|
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| SrBERTa (gold tokens) | 0.9300 | 0.0700 | 0.9187 | 0.0813 |
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|*SrBERTa (CLASSLA tokenizer)* | / | *0.0840* | / | *0.1024* |
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