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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: 0.2180 |
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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 | 0.57 | 1 | 1.7779 | 0.2727 | |
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| No log | 1.57 | 2 | 1.7088 | 0.3182 | |
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| No log | 2.57 | 3 | 1.5921 | 0.5455 | |
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| No log | 3.57 | 4 | 1.4587 | 0.5909 | |
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| No log | 4.57 | 5 | 1.3256 | 0.5455 | |
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| No log | 5.57 | 6 | 1.2211 | 0.5 | |
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| No log | 6.57 | 7 | 1.1066 | 0.6818 | |
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| No log | 7.57 | 8 | 0.9768 | 0.7727 | |
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| No log | 8.57 | 9 | 0.8590 | 0.8636 | |
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| No log | 9.57 | 10 | 0.7718 | 0.9091 | |
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| No log | 10.57 | 11 | 0.6999 | 0.9091 | |
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| No log | 11.57 | 12 | 0.6385 | 0.9091 | |
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| No log | 12.57 | 13 | 0.5761 | 0.9545 | |
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| No log | 13.57 | 14 | 0.5189 | 0.9545 | |
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| No log | 14.57 | 15 | 0.4646 | 0.9545 | |
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| No log | 15.57 | 16 | 0.4137 | 0.9091 | |
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| No log | 16.57 | 17 | 0.3679 | 0.9091 | |
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| No log | 17.57 | 18 | 0.3291 | 0.9091 | |
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| No log | 18.57 | 19 | 0.2937 | 0.9545 | |
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| 1.8863 | 19.57 | 20 | 0.2642 | 0.9545 | |
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| 1.8863 | 20.57 | 21 | 0.2366 | 0.9545 | |
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| 1.8863 | 21.57 | 22 | 0.2180 | 1.0 | |
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| 1.8863 | 22.57 | 23 | 0.2061 | 1.0 | |
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| 1.8863 | 23.57 | 24 | 0.1984 | 1.0 | |
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| 1.8863 | 24.57 | 25 | 0.1918 | 1.0 | |
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| 1.8863 | 25.57 | 26 | 0.1787 | 1.0 | |
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| 1.8863 | 26.57 | 27 | 0.1605 | 1.0 | |
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| 1.8863 | 27.57 | 28 | 0.1412 | 1.0 | |
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| 1.8863 | 28.57 | 29 | 0.1269 | 1.0 | |
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| 1.8863 | 29.57 | 30 | 0.1142 | 1.0 | |
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| 1.8863 | 30.57 | 31 | 0.1051 | 1.0 | |
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| 1.8863 | 31.57 | 32 | 0.0995 | 1.0 | |
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| 1.8863 | 32.57 | 33 | 0.0946 | 1.0 | |
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| 1.8863 | 33.57 | 34 | 0.0911 | 1.0 | |
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| 1.8863 | 34.57 | 35 | 0.0892 | 1.0 | |
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| 1.8863 | 35.57 | 36 | 0.0876 | 1.0 | |
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| 1.8863 | 36.57 | 37 | 0.0865 | 1.0 | |
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| 1.8863 | 37.57 | 38 | 0.0857 | 1.0 | |
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| 1.8863 | 38.57 | 39 | 0.0854 | 1.0 | |
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| 0.6775 | 39.57 | 40 | 0.0853 | 1.0 | |
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### Framework versions |
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- Transformers 4.21.3 |
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- Pytorch 1.12.1+cpu |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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