vit-base-patch16-224-9models – AI Model by pavanavn | AlphaNeural AI

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pavanavn/
vit-base-patch16-224-9models

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image-classification

generated_from_trainer

google/vit-base-patch16-224

autotrain_compatible

endpoints_compatible

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vit-base-patch16-224-9models

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

Loss: 0.0167
Accuracy: 0.9959

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: 0.0002
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5952	0.9790	35	0.2206	0.9344
0.1228	1.9860	71	0.0889	0.9754
0.1133	2.9930	107	0.0701	0.9816
0.0877	4.0	143	0.0808	0.9754
0.0597	4.9790	178	0.0234	0.9939
0.0718	5.9860	214	0.0325	0.9898
0.0666	6.9930	250	0.0459	0.9836
0.0467	8.0	286	0.0162	0.9959
0.0446	8.9790	321	0.0155	0.9959
0.0391	9.7902	350	0.0167	0.9959

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1