This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6729
Accuracy: 0.8868

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.8571	3	1.0830	0.3962
No log	2.0	7	1.0106	0.6415
1.0286	2.8571	10	0.9347	0.8302
1.0286	4.0	14	0.8509	0.8679
1.0286	4.8571	17	0.7853	0.8868
0.7956	6.0	21	0.7458	0.8868
0.7956	6.8571	24	0.7045	0.8679
0.7956	8.0	28	0.6863	0.8868
0.6554	8.5714	30	0.6729	0.8868

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1

soplac/art_classifier

art_classifier

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

soplac/
art_classifier