Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
stanford-cars-finetuned-vit – AI Model by DRSTRANGE1 | AlphaNeural AI
You can deploy this model and start earning money today!
DRSTRANGE1
/
stanford-cars-finetuned-vit
like
0
transformers
safetensors
vit
image-classification
generated_from_trainer
dima806/vehicle_10_types_image_detection
finetune
apache-2.0
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
stanford-cars-finetuned-vit
This model is a fine-tuned version of
dima806/vehicle_10_types_image_detection
on the None dataset. It achieves the following results on the evaluation set:
eval_loss: 0.6796
eval_accuracy: 0.8343
eval_f1: 0.8337
eval_runtime: 12.5247
eval_samples_per_second: 130.063
eval_steps_per_second: 2.076
epoch: 81.0735
step: 16539
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: 2e-05
train_batch_size: 32
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 100
mixed_precision_training: Native AMP
Framework versions
Transformers 4.56.1
Pytorch 2.8.0+cu128
Datasets 4.1.0
Tokenizers 0.22.0
