emotion_classification_v1.2

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emotion_classification_v1.2

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: 1.2401
• Accuracy: 0.625
• Precision: 0.6207
• Recall: 0.625
• F1: 0.6035

Model description

A slightly more accurate model compared to previous 1.1 version. More information needed

Intended uses & limitations

This model is fined tune solely for face emotion recognition.

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: 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: 15

Training results

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0
• Datasets 2.19.1
• Tokenizers 0.19.1