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

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deberta-v3-large-finetuned-augmentation-LUNAR-TAPT

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text-classification

generated_from_trainer

microsoft/deberta-v3-large

autotrain_compatible

endpoints_compatible

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deberta-v3-large-finetuned-augmentation-LUNAR-TAPT

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: 0.5533
F1: 0.8318
Roc Auc: 0.8690
Accuracy: 0.6467

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
0.3563	1.0	317	0.3408	0.7270	0.7871	0.4582
0.2479	2.0	634	0.3140	0.7602	0.8190	0.5292
0.1544	3.0	951	0.3197	0.7959	0.8429	0.5749
0.1019	4.0	1268	0.3359	0.8007	0.8498	0.5915
0.0594	5.0	1585	0.3837	0.8097	0.8503	0.6057
0.043	6.0	1902	0.4182	0.8095	0.8530	0.5994
0.034	7.0	2219	0.4901	0.7914	0.8334	0.5915
0.0311	8.0	2536	0.5068	0.8041	0.8447	0.6151
0.0118	9.0	2853	0.5300	0.8105	0.8559	0.6080
0.0072	10.0	3170	0.5500	0.8258	0.8604	0.6301
0.0084	11.0	3487	0.5559	0.8235	0.8614	0.6333
0.0012	12.0	3804	0.5533	0.8318	0.8690	0.6467
0.0023	13.0	4121	0.5862	0.8190	0.8590	0.6270
0.0008	14.0	4438	0.5803	0.8300	0.8671	0.6443
0.0004	15.0	4755	0.5811	0.8306	0.8681	0.6459
0.0003	16.0	5072	0.5844	0.8308	0.8688	0.6467

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0