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vit-base-patch16-224-in21k-cards-june-06-cropping-filtered-test – AI Model by ansilmbabl | AlphaNeural AI
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vit-base-patch16-224-in21k-cards-june-06-cropping-filtered-test
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transformers
safetensors
vit
image-classification
generated_from_trainer
google/vit-base-patch16-224-in21k
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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vit-base-patch16-224-in21k-cards-june-06-cropping-filtered-test
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:
eval_loss: 1.6758
eval_accuracy: 0.3141
eval_runtime: 71.2335
eval_samples_per_second: 140.383
eval_steps_per_second: 0.562
epoch: 5.9981
step: 779
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: 640
eval_batch_size: 256
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 5120
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
Framework versions
Transformers 4.41.2
Pytorch 2.0.1+cu117
Datasets 2.19.1
Tokenizers 0.19.1
