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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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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: delivery_truck_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: 0.9733333333333334 |
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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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# delivery_truck_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: 0.1787 |
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- Accuracy: 0.9733 |
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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: 60 |
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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 | 0.91 | 5 | 0.1787 | 0.9733 | |
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| No log | 1.91 | 10 | 0.1787 | 0.9733 | |
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| No log | 2.91 | 15 | 0.1787 | 0.9733 | |
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| 0.3799 | 3.91 | 20 | 0.1787 | 0.9733 | |
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| 0.3799 | 4.91 | 25 | 0.1787 | 0.9733 | |
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| 0.3799 | 5.91 | 30 | 0.1787 | 0.9733 | |
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| 0.3799 | 6.91 | 35 | 0.1787 | 0.9733 | |
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| 0.3648 | 7.91 | 40 | 0.1787 | 0.9733 | |
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| 0.3648 | 8.91 | 45 | 0.1787 | 0.9733 | |
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| 0.3648 | 9.91 | 50 | 0.1787 | 0.9733 | |
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| 0.3648 | 10.91 | 55 | 0.1787 | 0.9733 | |
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| 0.3954 | 11.91 | 60 | 0.1787 | 0.9733 | |
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| 0.3954 | 12.91 | 65 | 0.1787 | 0.9733 | |
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| 0.3954 | 13.91 | 70 | 0.1787 | 0.9733 | |
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| 0.3954 | 14.91 | 75 | 0.1787 | 0.9733 | |
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| 0.3926 | 15.91 | 80 | 0.1787 | 0.9733 | |
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| 0.3926 | 16.91 | 85 | 0.1787 | 0.9733 | |
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| 0.3926 | 17.91 | 90 | 0.1787 | 0.9733 | |
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| 0.3926 | 18.91 | 95 | 0.1787 | 0.9733 | |
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| 0.3801 | 19.91 | 100 | 0.1787 | 0.9733 | |
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| 0.3801 | 20.91 | 105 | 0.1787 | 0.9733 | |
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| 0.3801 | 21.91 | 110 | 0.1787 | 0.9733 | |
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| 0.3801 | 22.91 | 115 | 0.1787 | 0.9733 | |
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| 0.3815 | 23.91 | 120 | 0.1787 | 0.9733 | |
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| 0.3815 | 24.91 | 125 | 0.1787 | 0.9733 | |
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| 0.3815 | 25.91 | 130 | 0.1787 | 0.9733 | |
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| 0.3815 | 26.91 | 135 | 0.1787 | 0.9733 | |
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| 0.3955 | 27.91 | 140 | 0.1787 | 0.9733 | |
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| 0.3955 | 28.91 | 145 | 0.1787 | 0.9733 | |
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| 0.3955 | 29.91 | 150 | 0.1787 | 0.9733 | |
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| 0.3955 | 30.91 | 155 | 0.1787 | 0.9733 | |
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| 0.3854 | 31.91 | 160 | 0.1787 | 0.9733 | |
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| 0.3854 | 32.91 | 165 | 0.1787 | 0.9733 | |
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| 0.3854 | 33.91 | 170 | 0.1787 | 0.9733 | |
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| 0.3854 | 34.91 | 175 | 0.1787 | 0.9733 | |
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| 0.3949 | 35.91 | 180 | 0.1787 | 0.9733 | |
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| 0.3949 | 36.91 | 185 | 0.1787 | 0.9733 | |
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| 0.3949 | 37.91 | 190 | 0.1787 | 0.9733 | |
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| 0.3949 | 38.91 | 195 | 0.1787 | 0.9733 | |
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| 0.423 | 39.91 | 200 | 0.1787 | 0.9733 | |
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| 0.423 | 40.91 | 205 | 0.1787 | 0.9733 | |
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| 0.423 | 41.91 | 210 | 0.1787 | 0.9733 | |
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| 0.423 | 42.91 | 215 | 0.1787 | 0.9733 | |
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| 0.3761 | 43.91 | 220 | 0.1787 | 0.9733 | |
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| 0.3761 | 44.91 | 225 | 0.1787 | 0.9733 | |
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| 0.3761 | 45.91 | 230 | 0.1787 | 0.9733 | |
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| 0.3761 | 46.91 | 235 | 0.1787 | 0.9733 | |
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| 0.3673 | 47.91 | 240 | 0.1787 | 0.9733 | |
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| 0.3673 | 48.91 | 245 | 0.1787 | 0.9733 | |
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| 0.3673 | 49.91 | 250 | 0.1787 | 0.9733 | |
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| 0.3673 | 50.91 | 255 | 0.1787 | 0.9733 | |
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| 0.3639 | 51.91 | 260 | 0.1787 | 0.9733 | |
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| 0.3639 | 52.91 | 265 | 0.1787 | 0.9733 | |
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| 0.3639 | 53.91 | 270 | 0.1787 | 0.9733 | |
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| 0.3639 | 54.91 | 275 | 0.1787 | 0.9733 | |
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| 0.4031 | 55.91 | 280 | 0.1787 | 0.9733 | |
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| 0.4031 | 56.91 | 285 | 0.1787 | 0.9733 | |
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| 0.4031 | 57.91 | 290 | 0.1787 | 0.9733 | |
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| 0.4031 | 58.91 | 295 | 0.1787 | 0.9733 | |
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| 0.3787 | 59.91 | 300 | 0.1787 | 0.9733 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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