results – AI Model by Jialuo21 | AlphaNeural AI

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image-classification

generated_from_trainer

google/vit-base-patch16-224-in21k

autotrain_compatible

endpoints_compatible

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results

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:

Loss: 0.4185
Accuracy: 0.7551

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
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 256
total_eval_batch_size: 64
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4891	1.0	810	0.5060	0.7054
0.4271	2.0	1620	0.4423	0.7433
0.4216	2.9969	2427	0.4185	0.7551

Framework versions

Transformers 4.49.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.6.0
Tokenizers 0.21.0