This model is a fine-tuned version of beomi/kcbert-base on the LMH, the 10_class and the multi_labels datasets. It achieves the following results on the evaluation set:

Loss: 0.1303
Lrap: 0.8809

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Lrap
No log	1.0	235	0.1459	0.8585
No log	2.0	470	0.1265	0.8763
0.1694	3.0	705	0.1233	0.8798
0.1694	4.0	940	0.1285	0.8796
0.0767	5.0	1175	0.1303	0.8809

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1

parkjigwang/1008model

1008model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

parkjigwang/
1008model