deberta_sent4455 – AI Model by 1yuuuna | AlphaNeural AI

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1yuuuna/
deberta_sent4455

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text-classification

generated_from_trainer

kisti/korscideberta

autotrain_compatible

endpoints_compatible

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deberta_sent4455

This model is a fine-tuned version of kisti/korscideberta on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3113
Accuracy: 0.9066
Precision: 0.8995
Recall: 0.9066
F1: 0.9011

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: 1.5e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.32	0.3934	500	0.2873	0.8974	0.8870	0.8974	0.8878
0.284	0.7868	1000	0.2800	0.9022	0.8934	0.9022	0.8897
0.2797	1.1802	1500	0.2648	0.9037	0.8977	0.9037	0.8997
0.2759	1.5736	2000	0.2597	0.9107	0.9036	0.9107	0.9038
0.2746	1.9670	2500	0.2568	0.9100	0.9027	0.9100	0.9030
0.2523	2.3603	3000	0.3300	0.8793	0.8898	0.8793	0.8837
0.232	2.7537	3500	0.2753	0.9077	0.8999	0.9077	0.8996
0.217	3.1471	4000	0.2962	0.9096	0.9027	0.9096	0.9039
0.2265	3.5405	4500	0.2787	0.9107	0.9035	0.9107	0.9034
0.2094	3.9339	5000	0.2944	0.9085	0.9008	0.9085	0.8999
0.1933	4.3273	5500	0.3132	0.9066	0.8999	0.9066	0.9017
0.1935	4.7207	6000	0.3113	0.9066	0.8995	0.9066	0.9011

Framework versions

Transformers 4.45.0
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.20.3