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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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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: car_manufacturer_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: 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: 0.3394495412844037 |
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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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# car_manufacturer_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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7826 |
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- Accuracy: 0.3394 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 15 |
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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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| No log | 1.0 | 7 | 3.1387 | 0.2018 | |
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| 2.8998 | 2.0 | 14 | 3.1029 | 0.2018 | |
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| 2.7326 | 3.0 | 21 | 3.0453 | 0.2294 | |
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| 2.7326 | 4.0 | 28 | 3.0104 | 0.2385 | |
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| 2.5797 | 5.0 | 35 | 2.9655 | 0.2477 | |
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| 2.4873 | 6.0 | 42 | 2.9166 | 0.3211 | |
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| 2.4873 | 7.0 | 49 | 2.9122 | 0.2569 | |
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| 2.3408 | 8.0 | 56 | 2.8122 | 0.3119 | |
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| 2.2696 | 9.0 | 63 | 2.8159 | 0.3578 | |
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| 2.1527 | 10.0 | 70 | 2.8589 | 0.2752 | |
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| 2.1527 | 11.0 | 77 | 2.8248 | 0.2936 | |
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| 2.0649 | 12.0 | 84 | 2.7709 | 0.2936 | |
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| 2.0855 | 13.0 | 91 | 2.8183 | 0.2477 | |
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| 2.0855 | 14.0 | 98 | 2.7552 | 0.2569 | |
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| 1.9347 | 15.0 | 105 | 2.7826 | 0.3394 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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