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vit-emotion – AI Model by ubayhee007 | AlphaNeural AI
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ubayhee007
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vit-emotion
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transformers
safetensors
vit
image-classification
generated_from_trainer
imagefolder
google/vit-base-patch16-224
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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vit-emotion
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: 1.3013
Accuracy: 0.475
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: 16
eval_batch_size: 16
seed: 42
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: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.6375
1.0
40
1.5448
0.4125
0.9668
2.0
80
1.3493
0.45
0.5913
3.0
120
1.3013
0.475
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
