xlm-roberta-large-squad-ft-qa-ru-mt-to-uzn
This model is a fine-tuned version of deepset/xlm-roberta-large-squad2 on the med-alex/qa_mt_ru_to_uzn dataset.
Model description
This model is one of many models created within the framework of a project to study the solution of a QA task for low-resource languages using the example of Kazakh and Uzbek.
Please see the description of the project, where there is a description of the solution and the results of the models in order to choose the best model for the Kazakh or Uzbek language.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 28
- eval_batch_size: 28
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 5.0
Framework versions
- Transformers 4.40.1
- Pytorch 2.0.0+cu118
- Datasets 2.18.0
- Tokenizers 0.19.1
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Model tree for med-alex/xlm-roberta-large-squad-ft-qa-ru-mt-to-uzn
Base model
deepset/xlm-roberta-large-squad2