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bert_model_out – AI Model by Dannah | AlphaNeural AI
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Dannah
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bert_model_out
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transformers
tensorboard
safetensors
bert
text-classification
HHD
10_class
multi_labels
generated_from_trainer
beomi/kcbert-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert_model_out
This model is a fine-tuned version of
beomi/kcbert-base
on the unsmile_data dataset. It achieves the following results on the evaluation set:
Loss: 0.1869
Irap: 0.8724
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 7
Training results
Training Loss
Epoch
Step
Validation Loss
Irap
No log
1.0
235
0.1567
0.8739
No log
2.0
470
0.1518
0.8749
0.029
3.0
705
0.1718
0.8742
0.029
4.0
940
0.1803
0.8707
0.0165
5.0
1175
0.1808
0.8731
0.0165
6.0
1410
0.1850
0.8739
0.009
7.0
1645
0.1869
0.8724
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.0
Tokenizers 0.21.0
