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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- image-classification |
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- pytorch |
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datasets: |
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- cats_vs_dogs |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-cats-vs-dogs |
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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: cats_vs_dogs |
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type: cats_vs_dogs |
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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: 0.9934510250569476 |
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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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# vit-base-cats-vs-dogs |
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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 cats_vs_dogs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0202 |
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- Accuracy: 0.9935 |
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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: 0.0002 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 1337 |
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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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- num_epochs: 5.0 |
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- mixed_precision_training: Native AMP |
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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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| 0.064 | 1.0 | 311 | 0.0483 | 0.9849 | |
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| 0.0622 | 2.0 | 622 | 0.0275 | 0.9903 | |
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| 0.0366 | 3.0 | 933 | 0.0262 | 0.9917 | |
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| 0.0294 | 4.0 | 1244 | 0.0219 | 0.9932 | |
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| 0.0161 | 5.0 | 1555 | 0.0202 | 0.9935 | |
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### Framework versions |
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- Transformers 4.9.0 |
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- Pytorch 1.9.0+cu102 |
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- Datasets 1.11.1.dev0 |
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- Tokenizers 0.10.3 |
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