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roadSigns – AI Model by Bliu3 | AlphaNeural AI
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Bliu3
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roadSigns
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transformers
tensorboard
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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RoadSigns
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
on GTSRB dataset. It achieves the following results on the evaluation set:
Loss: 0.0871
Accuracy: 0.9914
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2187
1.0
612
0.2436
0.9888
0.0742
2.0
1225
0.1142
0.9888
0.0516
3.0
1836
0.0871
0.9914
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0
