Fashion Images Gender Age
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set: Loss: 0.0244 Accuracy: 0.9942
Modellquelle
- Art
- Other
- Dateigröße
- 327 MB
- Basismodell
- google/vit-base-patch16-224-in21k
- Version
- vRevision 89f032c
- Aktualisiert
- 6. Okt. 2026
- Downloads
- 27
- Quelle
- Hugging Face
Quellenbeschreibung
fashion-images-gender-age
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set:
- Loss: 0.0244
- Accuracy: 0.9942
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.167 | 1.0 | 2422 | 0.0796 | 0.9781 |
| 0.1169 | 2.0 | 4844 | 0.0480 | 0.9883 |
| 0.0993 | 3.0 | 7266 | 0.0264 | 0.9936 |
| 0.0738 | 4.0 | 9688 | 0.0244 | 0.9942 |
| 0.0497 | 5.0 | 12110 | 0.0297 | 0.9921 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 6. Okt.
Modellartefakte
1 Artefakt
Modellartefakte
1 ArtefaktQuellenauszüge
3 Auszüge
Quellenauszüge
3 Auszüge--- license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - image-classification - vision - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: fashion-images-gender-age results: - task: name: Image Classification type: image-classification dataset: name: touchtech/fashion-images-gender-age type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9941520467836257 --- <!-- 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. --> # fashion-images-gender-age This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set: - Loss: 0.0244 - Accuracy: 0.9942 ## 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: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 1337 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.167 | 1.0 | 2422 | 0.0796 | 0.9781 | | 0.1169 | 2.0 | 4844 | 0.0480 | 0.9883 | | 0.0993 | 3.0 | 7266 | 0.0264 | 0.9936 | | 0.0738 | 4.0 | 9688 | 0.0244 | 0.9942 | | 0.0497 | 5.0 | 12110 | 0.0297 | 0.9921 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
Source context: 27 downloads · 4 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-gender-age
Source context: 17 downloads · 4 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-gender-age
