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: 1.0169
Accuracy: 0.4737

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.8	1	1.1248	0.1053
No log	1.6	2	1.0913	0.3684
No log	2.4	3	1.0755	0.2632
No log	4.0	5	1.0527	0.3158
No log	4.8	6	1.0419	0.4211
No log	5.6	7	1.0168	0.4737
No log	6.4	8	1.0152	0.5263
1.0044	8.0	10	1.0169	0.4737

Framework versions

Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2

TenzinNYeshey/car-type-model

car-type-model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

TenzinNYeshey/
car-type-model