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klue_bert_base – AI Model by Woonn | AlphaNeural AI
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Woonn
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klue_bert_base
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
nsmc
cc-by-sa-4.0
model-index
autotrain_compatible
endpoints_compatible
us
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klue_bert_base
This model is a fine-tuned version of
klue/bert-base
on the nsmc dataset. It achieves the following results on the evaluation set:
Loss: 0.2415
Accuracy: 0.9056
F1: 0.9056
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.2742
1.0
2344
0.2381
0.9005
0.9005
0.1865
2.0
4688
0.2415
0.9056
0.9056
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2
