bert_model – AI Model by pnskmj1017 | AlphaNeural AI

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pnskmj1017/
bert_model

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text-classification

generated_from_trainer

beomi/kcbert-base

autotrain_compatible

endpoints_compatible

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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: 0.1301
Irap: 0.8817

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	Irap
No log	1.0	235	0.1491	0.8536
No log	2.0	470	0.1294	0.8707
0.1733	3.0	705	0.1230	0.8806
0.1733	4.0	940	0.1280	0.8783
0.0787	5.0	1175	0.1301	0.8817

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.0
Tokenizers 0.21.0