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
Downloads last month
10
Safetensors
Model size
85.8M params
Tensor type
F32
ยท
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Model tree for rbenrejeb/vit-Facial-Expression-Recognition

Finetuned
(19)
this model