| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - fair_face |
| metrics: |
| - accuracy |
| model-index: |
| - name: initial_ViT_model |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: fair_face |
| type: fair_face |
| config: '0.25' |
| split: validation |
| args: '0.25' |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.21252510498448055 |
| --- |
| |
| <!-- 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. --> |
|
|
| # initial_ViT_model |
|
|
| 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 fair_face dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 3.6347 |
| - Accuracy: 0.2125 |
| |
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 256 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.2 |
| - num_epochs: 1 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 4.7855 | 0.15 | 50 | 4.6444 | 0.0511 | |
| | 4.4242 | 0.29 | 100 | 4.2124 | 0.1418 | |
| | 4.0596 | 0.44 | 150 | 3.9402 | 0.1744 | |
| | 3.859 | 0.59 | 200 | 3.7823 | 0.1956 | |
| | 3.7392 | 0.74 | 250 | 3.6877 | 0.2105 | |
| | 3.6424 | 0.88 | 300 | 3.6347 | 0.2125 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
| |
