metadata

license: apache-2.0
base_model: rifkat/uztext-3Gb-BPE-Roberta
tags:
  - generated_from_trainer
  - roberta
model-index:
  - name: uzn-roberta-base-ft-qa-en-mt-to-uzn
    results: []
datasets:
  - med-alex/qa_mt_en_to_uzn
language:
  - uz
metrics:
  - exact_match
  - f1
library_name: transformers
pipeline_tag: question-answering

uzn-roberta-base-ft-qa-en-mt-to-uzn

This model is a fine-tuned version of rifkat/uztext-3Gb-BPE-Roberta on the None 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