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--- |
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datasets: |
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- hieupth/cad |
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- shreyanshu09/Block_Diagram |
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- krowiemlekommm/PJN_CHARTS |
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- corto-ai/handwritten-text |
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- katanaml-org/invoices-donut-data-v1 |
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- mathieu1256/FATURA2-invoices |
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- AjitRawat/invoice |
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- HuggingFaceM4/DocumentVQA |
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- ajaynmopidevi/DocumentIDEFICS_QA |
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- daitavan/financial-documents |
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- Anas989898/Vision-OCR-Financial-Reports-10k |
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- dpdl-benchmark/places100-easy |
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- xirigh/people |
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- huggan/flowers-102-categories |
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- iamkaikai/amazing_logos |
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- iamkaikai/amazing_logos_v2 |
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- manelreghima/companies_logos |
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- samp3209/logo-dataset |
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- salmonhumorous/logo-blip-caption |
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- dream-textures/textures-color-1k |
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- GATE-engine/describable_textures |
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- ppierzc/ios-app-icons |
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- Lancelot53/android_icon_dataset |
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- naxalpha/stable-icons-128 |
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- yaneivan/memes_caption |
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- Bruece/office-home-clipart-caption |
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base_model: |
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- timm/resnext50_32x4d.fb_swsl_ig1b_ft_in1k |
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--- |
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# fine_tuned_image_relevance_model |
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This model is a fine-tuned version of [resnext50_32x4d.fb_swsl_ig1b_ft_in1k](https://huggingface.co/timm/resnext50_32x4d.fb_swsl_ig1b_ft_in1k) on an aggregated dataset of images that were classified as relevant (1.0) or irrelevant (0.0). It achieves the following results on the validation set: |
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- Loss: 0.1032 |
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- Accuracy: 0.9936 |
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## Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 4e-06 |
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- train_batch_size: 8 |
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- valid_batch_size: 8 |
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- seed: seed not explicitly set |
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- optimizer: torch.optim.AdamW(resnet_model.parameters(), lr=lr, eps=0.000001) |
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- lr_scheduler_type: OneCycleLR |
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- num_epochs: 6 |
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## Training results |
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| Training Loss | Epoch | Validation Loss | Accuracy | |
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| :-----------: | :---: | :-------------: | :------: | |
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| 0.5536 | 1 | 0.3270 | 0.9856 | |
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| 0.3176 | 2 | 0.1720 | 0.9922 | |
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| 0.1887 | 3 | 0.1332 | 0.9944 | |
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| 0.1280 | 4 | 0.1146 | 0.9938 | |
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| 0.1116 | 5 | 0.1236 | 0.9938 | |
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| 0.1016 | 6 | 0.1032 | 0.9936 | |
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## Framework versions |
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- timm 1.0.19 |
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- PyTorch 2.8.0+cpu |
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- Datasets 4.0.0 |
