DeBERTaV3_model_V3_multilabel – AI Model by sergiomvazq | AlphaNeural AI

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sergiomvazq/
DeBERTaV3_model_V3_multilabel

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text-classification

generated_from_trainer

microsoft/deberta-v3-small

autotrain_compatible

endpoints_compatible

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DeBERTaV3_model_V3_multilabel

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

Loss: 0.0117
Accuracy: 0.9978
F1: 0.9985
Precision: 0.9970
Recall: 1.0

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: 5
eval_batch_size: 5
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 13

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	90	0.0239	0.9978	0.9985	0.9970	1.0
No log	2.0	180	0.0147	0.9978	0.9985	0.9970	1.0
No log	3.0	270	0.0131	0.9978	0.9985	0.9970	1.0
No log	4.0	360	0.0124	0.9978	0.9985	0.9970	1.0
No log	5.0	450	0.0121	0.9978	0.9985	0.9970	1.0
0.0608	6.0	540	0.0119	0.9978	0.9985	0.9970	1.0
0.0608	7.0	630	0.0117	0.9978	0.9985	0.9970	1.0
0.0608	8.0	720	0.0120	0.9978	0.9985	0.9970	1.0
0.0608	9.0	810	0.0127	0.9978	0.9985	0.9970	1.0
0.0608	10.0	900	0.0132	0.9978	0.9985	0.9970	1.0
0.0608	11.0	990	0.0139	0.9970	0.998	0.9970	0.9990
0.0121	12.0	1080	0.0143	0.9970	0.998	0.9970	0.9990
0.0121	13.0	1170	0.0143	0.9970	0.998	0.9970	0.9990

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.19.2
Tokenizers 0.19.1