Image Classification
timm
TensorBoard
vision
facial-expression-recognition
vit
vision-transformer
fer
ferplus
Instructions to use peepeeyanto/ViTFERPP_vit_small_patch16_224.augreg_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use peepeeyanto/ViTFERPP_vit_small_patch16_224.augreg_in1k with timm:
import timm model = timm.create_model("hf_hub:peepeeyanto/ViTFERPP_vit_small_patch16_224.augreg_in1k", pretrained=True) - Notebooks
- Google Colab
- Kaggle
File size: 889 Bytes
42b2077 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | Class Class_ID Precision Recall F1-Score Support
happy 3 0.918699 0.937759 0.928131 482
surprise 6 0.879310 0.796875 0.836066 128
angry 0 0.815789 0.849315 0.832215 73
sad 5 0.868750 0.727749 0.792023 191
neutral 4 0.724014 0.870690 0.790607 232
fear 2 0.647059 0.500000 0.564103 22
disgust 1 0.606557 0.506849 0.552239 73
================================================================================
OVERALL METRICS SUMMARY
================================================================================
Metric Score
Accuracy 0.836803
Precision (Macro) 0.780026
Precision (Weighted) 0.838746
Recall (Macro) 0.741320
Recall (Weighted) 0.836803
F1-Score (Macro) 0.756483
F1-Score (Weighted) 0.834761 |