deberta-v3-base-problematic-classifier – AI Model by adrienbrdne | AlphaNeural AI

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adrienbrdne/
deberta-v3-base-problematic-classifier

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text-classification

generated_from_trainer

microsoft/deberta-v3-base

autotrain_compatible

endpoints_compatible

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deberta-v3-base-problematic-classifier

This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3965
Accuracy: 0.878
Auc: 0.949

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: 9e-05
train_batch_size: 8
eval_batch_size: 8
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Auc
0.6782	1.0	263	0.6769	0.509	0.914
0.6296	2.0	526	0.5905	0.822	0.904
0.587	3.0	789	0.5380	0.829	0.919
0.5433	4.0	1052	0.5017	0.82	0.932
0.4995	5.0	1315	0.4558	0.842	0.941
0.4887	6.0	1578	0.4269	0.887	0.942
0.4638	7.0	1841	0.4143	0.867	0.944
0.4436	8.0	2104	0.3969	0.898	0.948
0.4387	9.0	2367	0.4003	0.873	0.948
0.434	10.0	2630	0.3965	0.878	0.949

Framework versions

Transformers 4.50.0.dev0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1