swin-tiny-patch4-window7-224-finetuned-fit – AI Model by xlagor | AlphaNeural AI

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xlagor/
swin-tiny-patch4-window7-224-finetuned-fit

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image-classification

generated_from_trainer

xlagor/swin-tiny-patch4-window7-224-finetuned-fit

autotrain_compatible

endpoints_compatible

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swin-tiny-patch4-window7-224-finetuned-fit

This model is a fine-tuned version of xlagor/swin-tiny-patch4-window7-224-finetuned-fit on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0711
Accuracy: 0.9772

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: 120
eval_batch_size: 120
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 480
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3727	0.99	62	0.1103	0.9680
0.3551	1.99	125	0.1018	0.9701
0.3258	3.0	188	0.0995	0.9706
0.3008	4.0	251	0.0939	0.9712
0.2896	4.99	313	0.0872	0.9730
0.2612	5.99	376	0.0829	0.9739
0.2275	7.0	439	0.0815	0.9748
0.2358	8.0	502	0.0839	0.9739
0.2191	8.99	564	0.0778	0.9775
0.2096	9.99	627	0.0759	0.9769
0.2063	11.0	690	0.0749	0.9778
0.1916	12.0	753	0.0735	0.9775
0.2002	12.99	815	0.0732	0.9781
0.1905	13.99	878	0.0713	0.9784
0.1835	15.0	941	0.0707	0.9784
0.1949	15.81	992	0.0711	0.9772

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3