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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: swin-food102 |
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results: [] |
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datasets: |
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- juliensimon/food102 |
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--- |
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# swin-food102 |
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This model is a fine-tuned version of [juliensimon/autotrain-food101-1471154053](https://huggingface.co/juliensimon/autotrain-food101-1471154053) on the [food102](https://huggingface.co/datasets/juliensimon/food102) dataset, namely the [food101](https://huggingface.co/datasets/food101) dataset with an extra class generated with a Stable Diffusion model. |
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A detailed walk-through is available on [YouTube](https://youtu.be/sIe0eo3fYQ4). |
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The achieves the following results on the evaluation set: |
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- Loss: 0.2510 |
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- Accuracy: 0.9338 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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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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- num_epochs: 3 |
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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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| 1.1648 | 1.0 | 597 | 0.3118 | 0.9218 | |
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| 0.31 | 2.0 | 1194 | 0.2606 | 0.9322 | |
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| 0.2488 | 3.0 | 1791 | 0.2510 | 0.9338 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu102 |
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- Datasets 2.4.0 |
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- Tokenizers 0.13.1 |
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