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kobart_naver – AI Model by memorygreen | AlphaNeural AI
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memorygreen
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kobart_naver
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transformers
safetensors
bart
text-classification
generated_from_trainer
gogamza/kobart-base-v2
finetune
mit
endpoints_compatible
us
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kobart_naver
This model is a fine-tuned version of
gogamza/kobart-base-v2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3548
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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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
0.3833
1.0
1000
0.3548
Framework versions
Transformers 5.10.2
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
