pretrained_result

This model is a fine-tuned version of motheecreator/vit-Facial-Expression-Recognition on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.6537
• Accuracy: 0.7843

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 OptimizerNames.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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6131	0.9904	90	0.6537	0.7843
0.5963	1.9904	180	0.6502	0.7824
0.5716	2.9904	270	0.6506	0.7783
0.5616	3.9904	360	0.6429	0.7821
0.5272	4.9904	450	0.6516	0.7772
0.5064	5.9904	540	0.6446	0.7764

Framework versions

• Transformers 4.48.2
• Pytorch 2.6.0+cu126
• Datasets 3.2.0
• Tokenizers 0.21.0