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emotion-detector – AI Model by hanphilc | AlphaNeural AI
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hanphilc
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emotion-detector
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transformers
safetensors
vit
image-classification
generated_from_trainer
imagefolder
google/vit-base-patch16-224
finetune
apache-2.0
model-index
endpoints_compatible
us
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emotion-detector
This model is a fine-tuned version of
google/vit-base-patch16-224
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.9393
Accuracy: 0.6499
F1: 0.6423
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: 5e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.9146
1.0
404
0.9393
0.6499
0.6423
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
