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amilah1605/
image_classification

Name: image_classification
Rating: 2.5 (5 reviews)

generated_from_trainer

google/vit-base-patch16-224-in21k

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image_classification

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

Loss: 1.5809
Accuracy: 0.45

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: 3e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.2
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.0715	1.0	10	2.0701	0.1313
2.0623	2.0	20	2.0531	0.2
2.0302	3.0	30	2.0127	0.25
1.9632	4.0	40	1.9530	0.2812
1.8736	5.0	50	1.8625	0.325
1.7788	6.0	60	1.7627	0.3625
1.677	7.0	70	1.7067	0.3625
1.5986	8.0	80	1.6461	0.4313
1.5581	9.0	90	1.6029	0.45
1.5082	10.0	100	1.6011	0.4188
1.4822	11.0	110	1.5765	0.4625
1.4599	12.0	120	1.5717	0.4562
1.451	13.0	130	1.5575	0.4313
1.446	14.0	140	1.5642	0.4125
1.4422	15.0	150	1.5705	0.4437

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu124
Tokenizers 0.21.0

amilah1605/image_classification

image_classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

amilah1605/
image_classification