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roberta-base-klue-ynat-classification – AI Model by Morgan9803 | AlphaNeural AI
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Morgan9803
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roberta-base-klue-ynat-classification
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
klue/bert-base
finetune
cc-by-sa-4.0
autotrain_compatible
endpoints_compatible
us
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Model card
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results
This model is a fine-tuned version of
klue/bert-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3885
Accuracy: 0.876
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: 8
eval_batch_size: 8
seed: 42
optimizer: Use 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
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4805
1.0
1250
0.4454
0.864
Framework versions
Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
