from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("klue/roberta-base")
tokenizer = AutoTokenizer.from_pretrained("klue/roberta-base")

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 256
eval_batch_size: 256
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	179	0.4838	0.8444
No log	2.0	358	0.3848	0.8659
0.4203	3.0	537	0.3778	0.8690
0.4203	4.0	716	0.3762	0.8702
0.4203	5.0	895	0.3747	0.8720

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

chunwoolee0/klue_ynat_roberta_base_model

klue_ynat_roberta_base_model

Model description

Intended uses & limitations

Training and evaluation data

How to use

Training procedure

Training hyperparameters

Training results

Framework versions

chunwoolee0/
klue_ynat_roberta_base_model