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

Loss: 1.2511
Accuracy: 0.635

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	50	1.8478	0.4263
No log	2.0	100	1.5582	0.4475
No log	3.0	150	1.3828	0.5837
No log	4.0	200	1.2861	0.6375
No log	5.0	250	1.2559	0.6412

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cpu
Datasets 2.17.0
Tokenizers 0.15.1

MONYETTERBANG/vit-emotions-fp16

vit-emotions-fp16

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MONYETTERBANG/
vit-emotions-fp16