license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags:

• generated_from_trainer datasets:
• imagefolder metrics:
• accuracy model-index:
• name: Emotion-Image-Classification-V2 results:
  • task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics:
    • name: Accuracy type: accuracy value: 0.59375

Emotion-Image-Classification-V2

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 1.2748
• Accuracy: 0.5938

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: 7e-07
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1750

Training results