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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-tiny-patch4-window7-224 |
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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: spa_images_classifier_jd_v1_convnext |
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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: 0.978066110596231 |
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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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# spa_images_classifier_jd_v1_convnext |
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co./microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0662 |
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- Accuracy: 0.9781 |
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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: 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: 10 |
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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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| 0.2494 | 1.0 | 227 | 0.1194 | 0.9555 | |
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| 0.2333 | 2.0 | 455 | 0.1008 | 0.9635 | |
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| 0.1977 | 3.0 | 683 | 0.0855 | 0.9703 | |
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| 0.1405 | 4.0 | 911 | 0.0792 | 0.9744 | |
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| 0.1575 | 5.0 | 1138 | 0.0734 | 0.9731 | |
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| 0.0948 | 6.0 | 1366 | 0.0666 | 0.9778 | |
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| 0.1049 | 7.0 | 1594 | 0.0662 | 0.9781 | |
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| 0.0928 | 8.0 | 1822 | 0.0693 | 0.9774 | |
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| 0.0903 | 9.0 | 2049 | 0.0704 | 0.9771 | |
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| 0.0759 | 9.97 | 2270 | 0.0652 | 0.9778 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.17.1 |
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- Tokenizers 0.14.1 |
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