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output – AI Model by 1yuuuna | AlphaNeural AI
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transformers
tensorboard
safetensors
deberta-v2
text-classification
generated_from_trainer
kisti/korscideberta
finetune
mit
autotrain_compatible
endpoints_compatible
us
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output
This model is a fine-tuned version of
kisti/korscideberta
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1835
Accuracy: 0.9280
Precision: 0.9280
Recall: 0.9280
F1: 0.9279
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: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.4034
0.3188
500
0.3371
0.8543
0.8737
0.8543
0.8538
0.2338
0.6376
1000
0.1964
0.9159
0.9159
0.9159
0.9159
0.2079
0.9563
1500
0.1719
0.9322
0.9323
0.9322
0.9323
Framework versions
Transformers 4.45.0
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.20.3
