PRE-deberta-v3-large-finetuned-augmentation – AI Model by sercetexam9 | AlphaNeural AI

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PRE-deberta-v3-large-finetuned-augmentation

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text-classification

generated_from_trainer

microsoft/deberta-v3-large

autotrain_compatible

endpoints_compatible

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PRE-deberta-v3-large-finetuned-augmentation

This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1785
F1: 0.7708
Roc Auc: 0.8731
Accuracy: 0.7941

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.2094	1.0	389	0.2261	0.5045	0.7268	0.6795
0.1726	2.0	778	0.1668	0.6900	0.8176	0.7445
0.1256	3.0	1167	0.1908	0.6485	0.7896	0.7336
0.1098	4.0	1556	0.1716	0.7544	0.8494	0.7876
0.0629	5.0	1945	0.1785	0.7708	0.8731	0.7941
0.0208	6.0	2334	0.2220	0.7648	0.8618	0.7889
0.02	7.0	2723	0.2273	0.7666	0.8513	0.7941
0.0121	8.0	3112	0.2406	0.7510	0.8517	0.7934

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0