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bert_model – AI Model by sssey | AlphaNeural AI
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sssey
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bert_model
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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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Model card
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bert_model
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: 0.1305
Lrap: 0.8800
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Lrap
No log
1.0
235
0.1479
0.8579
No log
2.0
470
0.1285
0.8726
0.1735
3.0
705
0.1231
0.8798
0.1735
4.0
940
0.1287
0.8798
0.0781
5.0
1175
0.1305
0.8800
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.0
Tokenizers 0.21.0
