output – AI Model by ginami | AlphaNeural AI

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token-classification

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beomi/KcELECTRA-base-v2022

autotrain_compatible

endpoints_compatible

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kcelectra_base_ner_law_v2

This model is a fine-tuned version of beomi/KcELECTRA-base-v2022 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0009

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: 3e-05
train_batch_size: 8
eval_batch_size: 64
seed: 15
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.0105	0.11	1000	0.0022
0.0028	0.22	2000	0.0019
0.0024	0.33	3000	0.0016
0.0014	0.44	4000	0.0027
0.0014	0.56	5000	0.0015
0.0016	0.67	6000	0.0013
0.0012	0.78	7000	0.0013
0.0016	0.89	8000	0.0011
0.0011	1.0	9000	0.0009
0.0006	1.11	10000	0.0013
0.0005	1.22	11000	0.0014

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Tokenizers 0.15.1