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: 0.2117
Accuracy: 0.9340

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: 0.0002
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
0.9707	0.9913	57	0.6825	0.8160
0.3507	2.0	115	0.3680	0.8909
0.2002	2.9913	172	0.3121	0.9023
0.1249	4.0	230	0.2951	0.9150
0.1002	4.9913	287	0.2596	0.9251
0.1014	6.0	345	0.2615	0.9251
0.1261	6.9913	402	0.2437	0.9365
0.0556	8.0	460	0.2198	0.9416
0.0415	8.9913	517	0.2119	0.9416
0.0294	9.9130	570	0.2117	0.9340

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1

pk3388/vit-base-patch16-224-ethosrealdata

vit-base-patch16-224-ethosrealdata

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

pk3388/
vit-base-patch16-224-ethosrealdata