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: 0.2285
Accuracy: 0.9970

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: 6e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
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	0.84	4	0.7136	0.9909
No log	1.89	9	0.4919	0.9939
0.6427	2.95	14	0.3749	0.9970
0.6427	4.0	19	0.3094	0.9939
0.3516	4.84	23	0.2767	0.9970
0.3516	5.89	28	0.2496	0.9970
0.2484	6.95	33	0.2357	0.9970
0.2484	8.0	38	0.2295	0.9970
0.2147	8.42	40	0.2285	0.9970

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

bluebird089/test-vit

test-vit

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

bluebird089/
test-vit