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vit-Facial-Expression-Recognition
kriskrishna/vit-Facial-Expression-Recognition
vit-Facial-Expression-Recognition is a image classification model from kriskrishna. Use it when you need a label for an image. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- Model type
- vit
- Access
- Public
- Created
- Oct 6, 2024
- Updated
- Oct 6, 2024
- SHA
- a062573c
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-Facial-Expression-Recognition
This model is a fine-tuned version of motheecreator/vit-Facial-Expression-Recognition on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1672
- Accuracy: 0.9320
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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7209 | 21.6216 | 100 | 0.5301 | 0.8155 |
| 0.0966 | 43.2432 | 200 | 0.1672 | 0.9320 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.20.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- Created
- Oct 6, 2024
- Updated
- Oct 6, 2024