car_orientation_classification – AI Model by ArrayDice | AlphaNeural AI | AlphaNeural AI

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ArrayDice/
car_orientation_classification

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image-classification

generated_from_trainer

google/vit-base-patch16-224-in21k

autotrain_compatible

endpoints_compatible

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car_orientation_classification2

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6800
Accuracy: 0.6926

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: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.9933	1.0	68	1.9084	0.4099
1.4721	2.0	136	1.2870	0.5124
1.1677	3.0	204	1.0780	0.5265
0.9919	4.0	272	0.9454	0.5760
0.8392	5.0	340	0.8184	0.6926
0.7778	6.0	408	0.8311	0.6431
0.7341	7.0	476	0.7425	0.6572
0.6695	8.0	544	0.6800	0.6926

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1