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vit-retro-modern-gaming – AI Model by gojkoana | AlphaNeural AI
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gojkoana
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vit-retro-modern-gaming
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transformers
tensorboard
safetensors
vit
image-classification
generated_from_trainer
imagefolder
google/vit-base-patch16-224
finetune
apache-2.0
model-index
endpoints_compatible
us
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vit-retro-modern-gaming
This model is a fine-tuned version of
google/vit-base-patch16-224
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.4590
Accuracy: 0.8333
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: 0.0003
train_batch_size: 16
eval_batch_size: 8
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
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
3
0.5552
0.6667
No log
2.0
6
0.4908
1.0
No log
3.0
9
0.4515
1.0
0.6364
4.0
12
0.4300
1.0
0.6364
5.0
15
0.4213
1.0
Framework versions
Transformers 5.5.4
Pytorch 2.11.0+cu130
Datasets 4.8.4
Tokenizers 0.22.2
