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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fair_face |
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metrics: |
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- accuracy |
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model-index: |
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- name: initial_ViT_model |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: fair_face |
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type: fair_face |
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config: '0.25' |
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split: validation |
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args: '0.25' |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.21252510498448055 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# initial_ViT_model |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6347 |
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- Accuracy: 0.2125 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 4.7855 | 0.15 | 50 | 4.6444 | 0.0511 | |
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| 4.4242 | 0.29 | 100 | 4.2124 | 0.1418 | |
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| 4.0596 | 0.44 | 150 | 3.9402 | 0.1744 | |
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| 3.859 | 0.59 | 200 | 3.7823 | 0.1956 | |
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| 3.7392 | 0.74 | 250 | 3.6877 | 0.2105 | |
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| 3.6424 | 0.88 | 300 | 3.6347 | 0.2125 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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