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vit-emotion-classifier
panjiallatief/vit-emotion-classifier
vit-emotion-classifier is a image classification model from panjiallatief. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- May 15, 2025
- Updated
- May 15, 2025
- SHA
- 58c8eb77
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
vit-emotion-classifier
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: 0.6218
- Accuracy: 0.8672
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: 0.0002
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6535 | 1.0 | 32 | 0.7740 | 0.7812 |
| 0.296 | 2.0 | 64 | 0.5949 | 0.8047 |
| 0.1542 | 3.0 | 96 | 0.6261 | 0.8047 |
| 0.0838 | 4.0 | 128 | 0.6315 | 0.8047 |
| 0.0189 | 5.0 | 160 | 0.8360 | 0.7656 |
| 0.0223 | 6.0 | 192 | 0.7264 | 0.8047 |
| 0.0114 | 7.0 | 224 | 0.8634 | 0.8047 |
| 0.0408 | 8.0 | 256 | 0.6393 | 0.8438 |
| 0.0075 | 9.0 | 288 | 0.7023 | 0.8438 |
| 0.006 | 10.0 | 320 | 0.6481 | 0.8516 |
| 0.0053 | 11.0 | 352 | 0.6247 | 0.8516 |
| 0.0047 | 12.0 | 384 | 0.6220 | 0.8594 |
| 0.0043 | 13.0 | 416 | 0.6186 | 0.8594 |
| 0.0041 | 14.0 | 448 | 0.6193 | 0.8594 |
| 0.0038 | 15.0 | 480 | 0.6205 | 0.8594 |
| 0.0036 | 16.0 | 512 | 0.6205 | 0.8594 |
| 0.0035 | 17.0 | 544 | 0.6218 | 0.8672 |
| 0.0034 | 18.0 | 576 | 0.6224 | 0.8672 |
| 0.0033 | 19.0 | 608 | 0.6229 | 0.8672 |
| 0.0033 | 20.0 | 640 | 0.6232 | 0.8672 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- May 15, 2025
- Updated
- May 15, 2025