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ko-mathbert – AI Model by jnsulee | AlphaNeural AI
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jnsulee
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ko-mathbert
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transformers
pytorch
tensorboard
bert
fill-mask
generated_from_trainer
cc-by-sa-4.0
autotrain_compatible
endpoints_compatible
us
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ko-mathbert
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: 2.6769
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: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
2.9461
1.0
157
2.8731
2.7776
2.0
314
2.7040
2.7261
3.0
471
2.6835
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2
