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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: 0.0942 |
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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: 40 |
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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 | 0.67 | 1 | 1.8688 | 0.1818 | |
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| No log | 1.67 | 2 | 1.7920 | 0.1818 | |
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| No log | 2.67 | 3 | 1.6533 | 0.3636 | |
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| No log | 3.67 | 4 | 1.4775 | 0.4545 | |
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| No log | 4.67 | 5 | 1.2912 | 0.5909 | |
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| No log | 5.67 | 6 | 1.1475 | 0.7273 | |
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| No log | 6.67 | 7 | 1.0266 | 0.7727 | |
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| No log | 7.67 | 8 | 0.9196 | 0.7727 | |
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| No log | 8.67 | 9 | 0.8273 | 0.8182 | |
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| No log | 9.67 | 10 | 0.7492 | 0.8182 | |
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| No log | 10.67 | 11 | 0.6857 | 0.9091 | |
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| No log | 11.67 | 12 | 0.6369 | 0.9091 | |
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| No log | 12.67 | 13 | 0.5916 | 1.0 | |
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| No log | 13.67 | 14 | 0.5462 | 1.0 | |
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| No log | 14.67 | 15 | 0.4927 | 1.0 | |
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| No log | 15.67 | 16 | 0.4390 | 1.0 | |
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| No log | 16.67 | 17 | 0.3914 | 1.0 | |
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| No log | 17.67 | 18 | 0.3446 | 1.0 | |
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| No log | 18.67 | 19 | 0.3019 | 1.0 | |
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| 1.7058 | 19.67 | 20 | 0.2611 | 1.0 | |
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| 1.7058 | 20.67 | 21 | 0.2289 | 1.0 | |
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| 1.7058 | 21.67 | 22 | 0.1960 | 1.0 | |
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| 1.7058 | 22.67 | 23 | 0.1711 | 1.0 | |
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| 1.7058 | 23.67 | 24 | 0.1568 | 1.0 | |
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| 1.7058 | 24.67 | 25 | 0.1463 | 1.0 | |
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| 1.7058 | 25.67 | 26 | 0.1383 | 1.0 | |
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| 1.7058 | 26.67 | 27 | 0.1323 | 1.0 | |
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| 1.7058 | 27.67 | 28 | 0.1268 | 1.0 | |
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| 1.7058 | 28.67 | 29 | 0.1199 | 1.0 | |
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| 1.7058 | 29.67 | 30 | 0.1145 | 1.0 | |
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| 1.7058 | 30.67 | 31 | 0.1129 | 1.0 | |
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| 1.7058 | 31.67 | 32 | 0.1095 | 1.0 | |
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| 1.7058 | 32.67 | 33 | 0.1079 | 1.0 | |
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| 1.7058 | 33.67 | 34 | 0.1053 | 1.0 | |
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| 1.7058 | 34.67 | 35 | 0.1034 | 1.0 | |
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| 1.7058 | 35.67 | 36 | 0.0990 | 1.0 | |
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| 1.7058 | 36.67 | 37 | 0.0963 | 1.0 | |
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| 1.7058 | 37.67 | 38 | 0.0952 | 1.0 | |
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| 1.7058 | 38.67 | 39 | 0.0944 | 1.0 | |
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| 0.6083 | 39.67 | 40 | 0.0942 | 1.0 | |
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### Framework versions |
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- Transformers 4.21.3 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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