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bert-base-finetuned-ynat – AI Model by yooonsangbeom | AlphaNeural AI
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bert-base-finetuned-ynat
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transformers
pytorch
bert
text-classification
generated_from_trainer
klue
klue/bert-base
finetune
cc-by-sa-4.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-base-finetuned-ynat
This model is a fine-tuned version of
klue/bert-base
on the klue dataset. It achieves the following results on the evaluation set:
Loss: 0.3691
Accuracy: 0.8659
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: 512
eval_batch_size: 512
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
90
0.4090
0.8599
No log
2.0
180
0.3929
0.8578
No log
3.0
270
0.3703
0.8648
No log
4.0
360
0.3714
0.8631
No log
5.0
450
0.3691
0.8659
Framework versions
Transformers 4.34.0
Pytorch 2.0.1+cu117
Datasets 2.13.1
Tokenizers 0.14.1
