emotion_recognition

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: 1.4479
• Accuracy: 0.475

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: 3e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	80	1.7877	0.3
No log	2.0	160	1.5989	0.4062
No log	3.0	240	1.4993	0.4313
No log	4.0	320	1.4446	0.4437
No log	5.0	400	1.4479	0.475
No log	6.0	480	1.4549	0.4437
0.6433	7.0	560	1.4635	0.45
0.6433	8.0	640	1.4767	0.4562
0.6433	9.0	720	1.4850	0.4437
0.6433	10.0	800	1.4864	0.4437

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1