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beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013
Celal11/beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013
beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013 is a image classification model from Celal11. 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
- beit
- Access
- Public
- Created
- Jan 8, 2023
- Updated
- Jan 9, 2023
- SHA
- c28d7d36
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. -->
beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013
This model is a fine-tuned version of Celal11/beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6185
- Accuracy: 0.7743
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9609 | 1.0 | 403 | 0.6678 | 0.7555 |
| 0.7786 | 2.0 | 806 | 0.6185 | 0.7743 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
- Task
- Image Classification
- Library
- transformers
- Type
- beit
- License
- apache-2.0
- Created
- Jan 8, 2023
- Updated
- Jan 9, 2023