각 언어별 f1_score
ko : f1_score = 0.8611821192789028
en : f1_score = 0.7868391074180795
ja : f1_score = 0.6440401846320934
es : f1_score = 0.8533862565120316

Intended uses & limitations

코드는 책을 활용 및 참고 하였습니다.

Training and evaluation data

XTREME 데이터 셋을 이용하였습니다. 특히 PAN-X 데이터 셋을 이용했습니다.

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 24
eval_batch_size: 24
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Score
0.5093	1.0	917	0.3530	0.7679
0.309	2.0	1834	0.3101	0.8029
0.2176	3.0	2751	0.3089	0.8140

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3

tommyjin/xlm-roberta-base-finetuned-panx-all-langs

xlm-roberta-base-finetuned-panx-all-langs

Model description

Intended uses & limitations

Training and evaluation data

Training hyperparameters

Training results

Framework versions

tommyjin/
xlm-roberta-base-finetuned-panx-all-langs