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roberta-base-klue-ynat-classification – AI Model by mjhwang | AlphaNeural AI
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mjhwang
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roberta-base-klue-ynat-classification
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transformers
safetensors
roberta
text-classification
generated_from_trainer
klue/roberta-base
finetune
autotrain_compatible
endpoints_compatible
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roberta-base-klue-ynat-classification
This model is a fine-tuned version of
klue/roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 1.0314
eval_model_preparation_time: 0.0027
eval_accuracy: 0.72
eval_runtime: 129.1224
eval_samples_per_second: 2.323
eval_steps_per_second: 0.294
step: 0
Model description
CPU 사용으로 인해 train데이터 700개로 줄여서 학습
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: 8
eval_batch_size: 8
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: 1
Framework versions
Transformers 4.54.0
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.2
