| | --- |
| | base_model: nateraw/vit-age-classifier |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - fair_face |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: image_age_classification |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: fair_face |
| | type: fair_face |
| | config: '0.25' |
| | split: train[:10000] |
| | args: '0.25' |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.601 |
| | --- |
| | |
| | <!-- 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](https://huggingface.co/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 |
| | |
