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vit-Facial-Expression-Recognition
NekoJar/vit-Facial-Expression-Recognition
vit-Facial-Expression-Recognition is a machine learning model from NekoJar. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- vit
- Access
- Public
- Created
- Dec 1, 2024
- Updated
- May 5, 2025
- SHA
- ee0413a9
Base models
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-Facial-Expression-Recognition
This model is a fine-tuned version of motheecreator/vit-Facial-Expression-Recognition on the None dataset. It achieves the following results on the evaluation set:
- Loss: 274615179022269209159025612029952.0000
- Accuracy: 0.2031
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
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 263990515307201053637938614632448.0000 | 1.1 | 100 | 274631465670911057443267253633024.0000 | 0.2030 |
| 261320303401263261122219774836736.0000 | 2.2 | 200 | 274623651174413068480281952911360.0000 | 0.2031 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
- Type
- vit
- Created
- Dec 1, 2024
- Updated
- May 5, 2025