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emotion_classification
aldidwiputra9/emotion_classification
emotion_classification is a image classification model from aldidwiputra9. 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
- vit
- Access
- Public
- Created
- Feb 16, 2024
- Updated
- Feb 16, 2024
- SHA
- 697e92f3
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. -->
emotion_classification
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: 1.5853
- Accuracy: 0.4625
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 20 | 1.9252 | 0.2938 |
| No log | 2.0 | 40 | 1.7439 | 0.4562 |
| No log | 3.0 | 60 | 1.6389 | 0.425 |
| No log | 4.0 | 80 | 1.5862 | 0.475 |
| No log | 5.0 | 100 | 1.5477 | 0.4188 |
| No log | 6.0 | 120 | 1.5441 | 0.4437 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cpu
- Datasets 2.17.0
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Feb 16, 2024
- Updated
- Feb 16, 2024