metadata
license: mit
base_model: timpal0l/mdeberta-v3-base-squad2
tags:
- generated_from_trainer
- mdeberta
model-index:
- name: mdeberta-base-squad-ft-qa-en-mt-to-kaz
results: []
datasets:
- med-alex/qa_mt_en_to_kaz
language:
- kk
metrics:
- exact_match
- f1
library_name: transformers
pipeline_tag: question-answering
mdeberta-base-squad-ft-qa-en-mt-to-kaz
This model is a fine-tuned version of timpal0l/mdeberta-v3-base-squad2 on the med-alex/qa_mt_en_to_kaz 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: 10.0
Framework versions
- Transformers 4.40.1
- Pytorch 2.0.0+cu118
- Datasets 2.18.0
- Tokenizers 0.19.1