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vitFaceExpression-HierachicalHead-CombinedAugmentation
mluger/vitFaceExpression-HierachicalHead-CombinedAugmentation
vitFaceExpression-HierachicalHead-CombinedAugmentation is a machine learning model from mluger. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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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Updated Apr 29, 2025
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At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Apr 29, 2025
- Updated
- Apr 29, 2025
- SHA
- 25dea5aa
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. -->
vitFaceExpression-HierachicalHead-CombinedAugmentation
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: 0.7441
- Accuracy: 0.6963
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: cosine
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0979 | 1.0 | 673 | 0.8969 | 0.6201 |
| 0.8571 | 2.0 | 1346 | 0.8009 | 0.6651 |
| 0.704 | 3.0 | 2019 | 0.7756 | 0.6733 |
| 0.6211 | 4.0 | 2692 | 0.7544 | 0.6799 |
| 0.5685 | 5.0 | 3365 | 0.7405 | 0.6957 |
| 0.4659 | 6.0 | 4038 | 0.7467 | 0.6939 |
| 0.422 | 7.0 | 4711 | 0.7449 | 0.6959 |
| 0.399 | 8.0 | 5384 | 0.7441 | 0.6963 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1
- Library
- transformers
- License
- apache-2.0
- Created
- Apr 29, 2025
- Updated
- Apr 29, 2025