deit-small-patch16-224-finetuned-HOMUS – AI Model by nadimkanazi | AlphaNeural AI | AlphaNeural AI

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nadimkanazi/
deit-small-patch16-224-finetuned-HOMUS

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image-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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deit-small-patch16-224-finetuned-HOMUS

This model is a fine-tuned version of facebook/deit-small-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2130
Accuracy: 0.9504
Precision: 0.9509
Recall: 0.9504
F1 Score: 0.9504

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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1 Score
0.8475	1.0	83	0.6638	0.8224	0.8304	0.8224	0.8206
0.26	1.99	166	0.3324	0.8917	0.8996	0.8917	0.8909
0.134	2.99	249	0.2342	0.9272	0.9292	0.9272	0.9265
0.0807	4.0	333	0.2153	0.9307	0.9314	0.9307	0.9301
0.0322	5.0	416	0.2077	0.9364	0.9383	0.9364	0.9364
0.0162	5.99	499	0.2255	0.9377	0.9389	0.9377	0.9377
0.0095	6.99	582	0.2147	0.9439	0.9446	0.9439	0.9439
0.0022	8.0	666	0.2185	0.95	0.9512	0.95	0.9500
0.0017	9.0	749	0.2117	0.9504	0.9509	0.9504	0.9504
0.0015	9.97	830	0.2130	0.9504	0.9509	0.9504	0.9504

Framework versions

Transformers 4.30.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.13.3