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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: swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification |
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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: 0.3924731182795699 |
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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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# swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification |
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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: 2.0567 |
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- Accuracy: 0.3925 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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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| No log | 0.8889 | 6 | 2.8975 | 0.1398 | |
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| 2.9658 | 1.9259 | 13 | 2.6866 | 0.2204 | |
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| 2.6529 | 2.9630 | 20 | 2.4370 | 0.3011 | |
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| 2.6529 | 4.0 | 27 | 2.2516 | 0.3495 | |
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| 2.3311 | 4.8889 | 33 | 2.1685 | 0.3710 | |
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| 2.1441 | 5.9259 | 40 | 2.0987 | 0.3656 | |
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| 2.1441 | 6.9630 | 47 | 2.0567 | 0.3925 | |
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| 2.0507 | 8.0 | 54 | 2.0416 | 0.3871 | |
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| 1.988 | 8.8889 | 60 | 2.0368 | 0.3763 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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