swin-base-patch4-window7-224-in22k-MM_Classification_base_V2 – AI Model by djbp | AlphaNeural AI

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djbp/
swin-base-patch4-window7-224-in22k-MM_Classification_base_V2

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image-classification

generated_from_trainer

microsoft/swin-base-patch4-window7-224-in22k

autotrain_compatible

endpoints_compatible

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swin-base-patch4-window7-224-in22k-MM_Classification_base_V2

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.3018
Accuracy: 0.8822

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: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 512
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0086	1.0	19	0.4613	0.8105
0.4528	2.0	38	0.3454	0.8592
0.3556	3.0	57	0.3289	0.8604
0.3404	4.0	76	0.3197	0.8784
0.3175	5.0	95	0.3018	0.8822
0.3007	6.0	114	0.3007	0.8809
0.2968	7.0	133	0.2967	0.8758

Framework versions

Transformers 4.43.3
Pytorch 1.13.1+cu117
Datasets 2.20.0
Tokenizers 0.19.1