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vit-Facial-Expression-Recognition – AI Model by shrestha1 | AlphaNeural AI
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shrestha1
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vit-Facial-Expression-Recognition
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transformers
safetensors
vit
image-classification
generated_from_trainer
imagefolder
mo-thecreator/vit-Facial-Expression-Recognition
finetune
model-index
autotrain_compatible
endpoints_compatible
us
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vit-Facial-Expression-Recognition
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: 0.2561
Accuracy: 0.9135
F1: 0.9137
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.5281
0.8909
100
0.2554
0.9131
0.9118
0.5278
1.7751
200
0.2535
0.9136
0.9127
0.4992
2.6592
300
0.2602
0.9107
0.9085
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
