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Greek Longformer

A Greek version of the Longformer Language Model.

This model is a (from scratch) Greek Longformer model based on the configuration of allenai/longformer-base-4096, and trained on the combined datasets from the Greek Wikipedia and the Greek part of OSCAR. It achieves the following results on the evaluation set:

• Loss: 1.1080
• Accuracy: 0.7765

Pre-training corpora

The pre-training corpora of greek-longformer-base-4096 include:

• The Greek part of Wikipedia,
• The Greek part of OSCAR, a cleansed version of Common Crawl.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 6.0

Training results

Framework versions

• Transformers 4.28.0.dev0
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.2

Citing & Authors

The model has been officially released with the article "From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning". Dimitrios Zaikis and Ioannis Vlahavas. In: IEEE Access.

If you use the model, please cite the following:

@ARTICLE{10288436,
    author =  {Zaikis, Dimitrios and Vlahavas, Ioannis},
    journal = {IEEE Access},
    title =   {From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning},
    year =    {2023},
    volume =  {},
    number =  {},
    pages =   {1-1},
    doi =     {10.1109/ACCESS.2023.3326337}
  }