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vit-Facial-Expression-Recognition – AI Model by Alpiyildo | AlphaNeural AI
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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: 0.2631
Accuracy: 0.9177
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5315
0.8909
100
0.2603
0.9184
0.5202
1.7817
200
0.2583
0.9181
0.4912
2.6726
300
0.2609
0.9171
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
