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vit-base-patch16-224-in21k-lora – AI Model by geshijoker | AlphaNeural AI
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geshijoker
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vit-base-patch16-224-in21k-lora
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peft
tensorboard
safetensors
generated_from_trainer
google/vit-base-patch16-224-in21k
adapter
apache-2.0
us
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vit-base-patch16-224-in21k-lora
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
on food101 dataset. It achieves the following results on the evaluation set:
trainable params: 667,493 || all params: 86,543,818 || trainable%: 0.7713
Loss: 0.3400
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.005
train_batch_size: 256
eval_batch_size: 256
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 1024
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.8448
1.0
74
0.4689
0.7281
2.0
148
0.4009
0.6533
3.0
222
0.3697
0.5799
4.0
296
0.3520
0.5547
5.0
370
0.3400
Framework versions
PEFT 0.11.1
Transformers 4.43.4
Pytorch 2.2.1+cu118
Datasets 2.21.0
Tokenizers 0.19.1
