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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-patch16-224-vit-base-patch16 |
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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: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5851995594482614 |
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--- |
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# Caracam (gen 1) |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9156 |
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- Accuracy: 0.5852 |
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## Model description |
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First generation of my AI that tells you what car you took a picture of. \ |
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More versions coming soon with accuracy ratings of 85% and higher! Trained on 70+ brands with 2700+ cars going from 1945-2024. \ |
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***App coming soon (also called Caracam) to Android and IOS*** \ |
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(Late March - Early April 2024). |
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In the future I will take user opinion into account on what brands to add. The app will be updated semi-yearly with user-suggested car brands! \ |
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if you wish to support project Caracam please visit my [Patreon](https://www.patreon.com/Caracam) or my [Cashapp](https://cash.app/$Clippayy)!! |
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## Intended uses & limitations |
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***NOT FOR COMMERCIAL USE OUTSIDE OF OFFICIAL CARACAM MOBILE APP*** |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 0.1 |
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- num_epochs: 3 |
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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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| 4.0308 | 1.0 | 5362 | 3.6948 | 0.2491 | |
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| 2.694 | 2.0 | 10725 | 2.2586 | 0.5199 | |
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| 2.4475 | 3.0 | 16086 | 1.9156 | 0.5852 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cpu |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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