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izeeek/
image_classification

tensorboard

safetensors

vit

generated_from_trainer

imagefolder

google/vit-base-patch16-224-in21k

finetune

apache-2.0

model-index

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image_classification

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 1.2364
Accuracy: 0.5938

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.0702	1.0	10	2.0666	0.1437
2.0583	2.0	20	2.0476	0.2125
2.0291	3.0	30	2.0018	0.3
1.9639	4.0	40	1.9175	0.3563
1.8582	5.0	50	1.7997	0.4375
1.7385	6.0	60	1.6756	0.4625
1.5984	7.0	70	1.5469	0.4625
1.4739	8.0	80	1.4684	0.5188
1.3737	9.0	90	1.4090	0.5125
1.2719	10.0	100	1.3740	0.525
1.2072	11.0	110	1.3527	0.55
1.1158	12.0	120	1.3118	0.5188
1.0487	13.0	130	1.2349	0.6
0.9873	14.0	140	1.2931	0.525
0.8928	15.0	150	1.2731	0.55

Framework versions

Transformers 4.42.4
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

izeeek/image_classification

image_classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

izeeek/
image_classification