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--- |
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language: |
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- el |
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tags: |
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- text |
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- language-modeling |
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datasets: |
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- dataset/wiki_oscar_combined_normalized_uncased |
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metrics: |
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- accuracy |
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model-index: |
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- name: greek-longformer-base-4096 |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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dataset: |
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name: dataset/wiki_oscar_combined_normalized_uncased |
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type: dataset/wiki_oscar_combined_normalized_uncased |
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split: None |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7765486725663717 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Greek Longformer |
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A Greek version of the Longformer Language Model. |
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This model is a (from scratch) Greek Longformer model based on the configuration of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096), and trained on the combined datasets from the [Greek Wikipedia](https://huggingface.co/datasets/wikipedia) and the Greek part of [OSCAR](https://huggingface.co/datasets/oscar-corpus/OSCAR-2301). |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1080 |
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- Accuracy: 0.7765 |
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## Pre-training corpora |
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The pre-training corpora of `greek-longformer-base-4096` include: |
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- The Greek part of [Wikipedia](https://el.wikipedia.org/wiki/Βικιπαίδεια:Αντίγραφα_της_βάσης_δεδομένων), |
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- The Greek part of [OSCAR](https://traces1.inria.fr/oscar/), a cleansed version of [Common Crawl](https://commoncrawl.org). |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 6.0 |
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### Training results |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.2 |
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## Citing & Authors |
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The model has been officially released with the article "From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning". |
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Dimitrios Zaikis and Ioannis Vlahavas. |
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In: IEEE Access. |
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If you use the model, please cite the following: |
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```bibtex |
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@ARTICLE{10288436, |
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author = {Zaikis, Dimitrios and Vlahavas, Ioannis}, |
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journal = {IEEE Access}, |
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title = {From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning}, |
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year = {2023}, |
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volume = {}, |
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number = {}, |
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pages = {1-1}, |
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doi = {10.1109/ACCESS.2023.3326337} |
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} |
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``` |
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