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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: 1.0 |
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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: 0.0290 |
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- Accuracy: 1.0 |
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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 | 0.94 | 4 | 0.0290 | 1.0 | |
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| No log | 1.94 | 8 | 0.0290 | 1.0 | |
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| No log | 2.94 | 12 | 0.0290 | 1.0 | |
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| No log | 3.94 | 16 | 0.0290 | 1.0 | |
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| 0.2595 | 4.94 | 20 | 0.0290 | 1.0 | |
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| 0.2595 | 5.94 | 24 | 0.0290 | 1.0 | |
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| 0.2595 | 6.94 | 28 | 0.0290 | 1.0 | |
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| 0.2595 | 7.94 | 32 | 0.0290 | 1.0 | |
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| 0.2595 | 8.94 | 36 | 0.0290 | 1.0 | |
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| 0.2679 | 9.94 | 40 | 0.0290 | 1.0 | |
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| 0.2679 | 10.94 | 44 | 0.0290 | 1.0 | |
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| 0.2679 | 11.94 | 48 | 0.0290 | 1.0 | |
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| 0.2679 | 12.94 | 52 | 0.0290 | 1.0 | |
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| 0.2679 | 13.94 | 56 | 0.0290 | 1.0 | |
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| 0.275 | 14.94 | 60 | 0.0290 | 1.0 | |
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| 0.275 | 15.94 | 64 | 0.0290 | 1.0 | |
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| 0.275 | 16.94 | 68 | 0.0290 | 1.0 | |
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| 0.275 | 17.94 | 72 | 0.0290 | 1.0 | |
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| 0.275 | 18.94 | 76 | 0.0290 | 1.0 | |
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| 0.248 | 19.94 | 80 | 0.0290 | 1.0 | |
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| 0.248 | 20.94 | 84 | 0.0290 | 1.0 | |
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| 0.248 | 21.94 | 88 | 0.0290 | 1.0 | |
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| 0.248 | 22.94 | 92 | 0.0290 | 1.0 | |
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| 0.248 | 23.94 | 96 | 0.0290 | 1.0 | |
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| 0.2669 | 24.94 | 100 | 0.0290 | 1.0 | |
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| 0.2669 | 25.94 | 104 | 0.0290 | 1.0 | |
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| 0.2669 | 26.94 | 108 | 0.0290 | 1.0 | |
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| 0.2669 | 27.94 | 112 | 0.0290 | 1.0 | |
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| 0.2669 | 28.94 | 116 | 0.0290 | 1.0 | |
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| 0.2589 | 29.94 | 120 | 0.0290 | 1.0 | |
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| 0.2589 | 30.94 | 124 | 0.0290 | 1.0 | |
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| 0.2589 | 31.94 | 128 | 0.0290 | 1.0 | |
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| 0.2589 | 32.94 | 132 | 0.0290 | 1.0 | |
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| 0.2589 | 33.94 | 136 | 0.0290 | 1.0 | |
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| 0.278 | 34.94 | 140 | 0.0290 | 1.0 | |
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| 0.278 | 35.94 | 144 | 0.0290 | 1.0 | |
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| 0.278 | 36.94 | 148 | 0.0290 | 1.0 | |
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| 0.278 | 37.94 | 152 | 0.0290 | 1.0 | |
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| 0.278 | 38.94 | 156 | 0.0290 | 1.0 | |
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| 0.273 | 39.94 | 160 | 0.0290 | 1.0 | |
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| 0.273 | 40.94 | 164 | 0.0290 | 1.0 | |
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| 0.273 | 41.94 | 168 | 0.0290 | 1.0 | |
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| 0.273 | 42.94 | 172 | 0.0290 | 1.0 | |
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| 0.273 | 43.94 | 176 | 0.0290 | 1.0 | |
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| 0.2535 | 44.94 | 180 | 0.0290 | 1.0 | |
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| 0.2535 | 45.94 | 184 | 0.0290 | 1.0 | |
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| 0.2535 | 46.94 | 188 | 0.0290 | 1.0 | |
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| 0.2535 | 47.94 | 192 | 0.0290 | 1.0 | |
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| 0.2535 | 48.94 | 196 | 0.0290 | 1.0 | |
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| 0.2762 | 49.94 | 200 | 0.0290 | 1.0 | |
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| 0.2762 | 50.94 | 204 | 0.0290 | 1.0 | |
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| 0.2762 | 51.94 | 208 | 0.0290 | 1.0 | |
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| 0.2762 | 52.94 | 212 | 0.0290 | 1.0 | |
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| 0.2762 | 53.94 | 216 | 0.0290 | 1.0 | |
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| 0.2798 | 54.94 | 220 | 0.0290 | 1.0 | |
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| 0.2798 | 55.94 | 224 | 0.0290 | 1.0 | |
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| 0.2798 | 56.94 | 228 | 0.0290 | 1.0 | |
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| 0.2798 | 57.94 | 232 | 0.0290 | 1.0 | |
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| 0.2798 | 58.94 | 236 | 0.0290 | 1.0 | |
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| 0.2709 | 59.94 | 240 | 0.0290 | 1.0 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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