vit-Facial-Expression-Recognition

This model is a fine-tuned version of motheecreator/vit-Facial-Expression-Recognition on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3720
• Accuracy: 0.8732

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 256
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 1000
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5752	0.2164	100	0.3737	0.8740
0.568	0.4328	200	0.3759	0.8720
0.551	0.6492	300	0.3722	0.8734
0.5604	0.8656	400	0.3747	0.8733
0.5391	1.0820	500	0.3720	0.8732
0.5751	1.2984	600	0.3761	0.8718
0.5678	1.5147	700	0.3824	0.8691
0.5493	1.7311	800	0.3870	0.8672
0.5766	1.9475	900	0.3942	0.8629
0.5301	2.1639	1000	0.3947	0.8639
0.5092	2.3803	1100	0.3896	0.8656
0.5164	2.5967	1200	0.3778	0.8703
0.4971	2.8131	1300	0.3731	0.8730

Framework versions

• Transformers 4.46.3
• Pytorch 2.4.0
• Datasets 3.1.0
• Tokenizers 0.20.3