farhanyh/emotion-classification

results

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: 1.2636
• Accuracy: 0.5125

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	20	1.9736	0.225
No log	2.0	40	1.7481	0.2687
No log	3.0	60	1.6042	0.3187
No log	4.0	80	1.5067	0.4062
No log	5.0	100	1.4777	0.3875
No log	6.0	120	1.4160	0.4437
No log	7.0	140	1.3415	0.4875
No log	8.0	160	1.3274	0.4813
No log	9.0	180	1.3460	0.4938
No log	10.0	200	1.3201	0.5
No log	11.0	220	1.2853	0.5125
No log	12.0	240	1.2671	0.5312
No log	13.0	260	1.2979	0.5062
No log	14.0	280	1.2755	0.575
No log	15.0	300	1.2490	0.5312

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3