swinv2-large-patch4-window12-192-22k-augmented – AI Model by canadianjosieharrison | AlphaNeural AI

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canadianjosieharrison/
swinv2-large-patch4-window12-192-22k-augmented

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image-classification

generated_from_trainer

microsoft/swinv2-large-patch4-window12-192-22k

autotrain_compatible

endpoints_compatible

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swinv2-large-patch4-window12-192-22k-augmented

This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12-192-22k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.3067
Accuracy: 0.8723

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: 0.0001
train_batch_size: 48
eval_batch_size: 48
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 384
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
No log	0.89	3	1.4847	0.5816
No log	1.78	6	0.9256	0.6950
1.2457	2.96	10	0.6017	0.7589
1.2457	3.85	13	0.3806	0.8723
1.2457	4.74	16	0.3866	0.8440
0.3656	5.93	20	0.3358	0.8794
0.3656	6.81	23	0.2803	0.8865
0.3656	8.0	27	0.3079	0.8723
0.2205	8.89	30	0.3067	0.8723

Framework versions

Transformers 4.35.0
Pytorch 2.1.1+cu118
Datasets 2.14.6
Tokenizers 0.14.1