| --- |
| tags: |
| language: |
| - grc |
| model-index: |
| - name: aristoBERTo |
| results: [] |
| widget: |
| - text: "Πλάτων ὁ Περικτιόνης [MASK] γένος ἀνέφερεν εἰς Σόλωνα." |
| - text: "ὁ Κριτίας ἀπέβλεψε [MASK] τὴν θύραν." |
| - text: "πρῶτοι δὲ καὶ οὐνόματα ἱρὰ ἔγνωσαν καὶ [MASK] ἱροὺς ἔλεξαν." |
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|
| --- |
| |
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| # aristoBERTo |
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| aristoBERTo is a transformer model for ancient Greek, a low resource language. We initialized the pre-training with weights from [GreekBERT](https://huggingface.co/nlpaueb/bert-base-greek-uncased-v1), a Greek version of BERT which was trained on a large corpus of modern Greek (~ 30 GB of texts). We continued the pre-training with an ancient Greek corpus of about 900 MB, which was scrapped from the web and post-processed. Duplicate texts and editorial punctuation were removed. |
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| Applied to the processing of ancient Greek, aristoBERTo outperforms xlm-roberta-base and mdeberta in most downstream tasks like the labeling of POS, MORPH, DEP and LEMMA. |
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| aristoBERTo is provided by the [Diogenet project](https://diogenet.ucsd.edu) of the University of California, San Diego. |
| |
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| ## Intended uses |
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| This model was created for fine-tuning with spaCy and the ancient Greek Universal Dependency datasets as well as a NER corpus produced by the [Diogenet project](https://diogenet.ucsd.edu). As a fill-mask model, AristoBERTo can also be used in the restoration of damaged Greek papyri, inscriptions, and manuscripts. |
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| It achieves the following results on the evaluation set: |
| - Loss: 1.6323 |
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| ## Training procedure |
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| ### Training hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20.0 |
| - mixed_precision_training: Native AMP |
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| ### Training results |
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| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:-------:|:---------------:| |
| | 1.377 | 20.0 | 3414220 | 1.6314 | |
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| ### Framework versions |
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| - Transformers 4.14.0.dev0 |
| - Pytorch 1.10.0+cu102 |
| - Datasets 1.16.1 |
| - Tokenizers 0.10.3 |
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