This model is a fine-tuned version of monologg/koelectra-base-v3-discriminator on the klue-ynat dataset. It achieves the following results on the evaluation set:

Loss: 0.4564
Accuracy: 0.0
Precision: 0.0
Recall: 0.0
F1score: 0.0

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: 64
eval_batch_size: 64
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
0.3953	1.0	714	0.4564
0.3035	2.0	1428	0.3919
0.2089	3.0	2142	0.4142

Framework versions

Transformers 4.54.1
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.4

dasein0/ynat-model

ynat-model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dasein0/
ynat-model