bert_model_result – AI Model by dynncat | AlphaNeural AI

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dynncat/
bert_model_result

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text-classification

generated_from_trainer

beomi/kcbert-base

autotrain_compatible

endpoints_compatible

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bert_model_result

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: 0.1646
Lrap: 0.8742

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 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	Lrap
No log	1.0	235	0.1287	0.8744
No log	2.0	470	0.1332	0.8779
0.0658	3.0	705	0.1450	0.8776
0.0658	4.0	940	0.1533	0.8740
0.0319	5.0	1175	0.1569	0.8757
0.0319	6.0	1410	0.1632	0.8715
0.018	7.0	1645	0.1646	0.8742

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.3.0
Tokenizers 0.21.0