metadata

license: mit
base_model: xlm-roberta-large
tags:
  - generated_from_trainer
model-index:
  - name: EthioLLM-l-250K
    results: []
language:
  - am
  - om
  - ti
  - so
  - gez

EthioLLM-l-250K

This model is a fine-tuned version of xlm-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.0552

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: 10
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0

Training results

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3

Citation Information

@article{tonja2024ethiollm, title={EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation}, author={Tonja, Atnafu Lambebo and Azime, Israel Abebe and Belay, Tadesse Destaw and Yigezu, Mesay Gemeda and Mehamed, Moges Ahmed and Ayele, Abinew Ali and Jibril, Ebrahim Chekol and Woldeyohannis, Michael Melese and Kolesnikova, Olga and Slusallek, Philipp and others}, journal={arXiv preprint arXiv:2403.13737}, year={2024} }