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image_age_classification
dini-r-a/image_age_classification
image_age_classification is a image classification model from dini-r-a. 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
- Sep 12, 2023
- Updated
- Sep 13, 2023
- SHA
- 9d00522a
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. -->
image_age_classification
This model is a fine-tuned version of nateraw/vit-age-classifier on the fair_face dataset. It achieves the following results on the evaluation set:
- Loss: 0.9464
- Accuracy: 0.601
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9107 | 1.0 | 125 | 0.9360 | 0.6065 |
| 0.7945 | 2.0 | 250 | 0.9545 | 0.588 |
| 1.0256 | 3.0 | 375 | 1.0144 | 0.586 |
| 0.7354 | 4.0 | 500 | 0.9726 | 0.594 |
| 0.6979 | 5.0 | 625 | 0.9735 | 0.5995 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.14.5
- Tokenizers 0.12.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- Created
- Sep 12, 2023
- Updated
- Sep 13, 2023