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vit-Facial-Expression-Recognition
Alpiyildo/vit-Facial-Expression-Recognition
vit-Facial-Expression-Recognition is a image classification model from Alpiyildo. 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
- Jul 9, 2024
- Updated
- Jul 16, 2024
- SHA
- 84737721
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: 0.2631
- Accuracy: 0.9177
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 |
|---|---|---|---|---|
| 0.5315 | 0.8909 | 100 | 0.2603 | 0.9184 |
| 0.5202 | 1.7817 | 200 | 0.2583 | 0.9181 |
| 0.4912 | 2.6726 | 300 | 0.2609 | 0.9171 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- Created
- Jul 9, 2024
- Updated
- Jul 16, 2024