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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: 0.8571428571428571 |
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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: 0.7036 |
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- Accuracy: 0.8571 |
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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 | 1.0 | 1 | 1.9875 | 0.1429 | |
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| No log | 2.0 | 2 | 1.9132 | 0.1429 | |
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| No log | 3.0 | 3 | 1.7585 | 0.4286 | |
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| No log | 4.0 | 4 | 1.5935 | 0.4286 | |
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| No log | 5.0 | 5 | 1.5026 | 0.4286 | |
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| No log | 6.0 | 6 | 1.4699 | 0.4286 | |
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| No log | 7.0 | 7 | 1.4361 | 0.4286 | |
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| No log | 8.0 | 8 | 1.3962 | 0.4286 | |
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| No log | 9.0 | 9 | 1.3457 | 0.4286 | |
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| No log | 10.0 | 10 | 1.2874 | 0.4286 | |
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| No log | 11.0 | 11 | 1.2240 | 0.4286 | |
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| No log | 12.0 | 12 | 1.1643 | 0.4286 | |
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| No log | 13.0 | 13 | 1.1016 | 0.5714 | |
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| No log | 14.0 | 14 | 1.0356 | 0.5714 | |
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| No log | 15.0 | 15 | 0.9719 | 0.7143 | |
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| No log | 16.0 | 16 | 0.9120 | 0.7143 | |
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| No log | 17.0 | 17 | 0.8606 | 0.7143 | |
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| No log | 18.0 | 18 | 0.8117 | 0.7143 | |
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| No log | 19.0 | 19 | 0.7707 | 0.7143 | |
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| 0.5111 | 20.0 | 20 | 0.7367 | 0.7143 | |
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| 0.5111 | 21.0 | 21 | 0.7157 | 0.7143 | |
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| 0.5111 | 22.0 | 22 | 0.7067 | 0.7143 | |
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| 0.5111 | 23.0 | 23 | 0.7012 | 0.7143 | |
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| 0.5111 | 24.0 | 24 | 0.6977 | 0.7143 | |
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| 0.5111 | 25.0 | 25 | 0.6974 | 0.7143 | |
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| 0.5111 | 26.0 | 26 | 0.6977 | 0.7143 | |
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| 0.5111 | 27.0 | 27 | 0.7036 | 0.8571 | |
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| 0.5111 | 28.0 | 28 | 0.7074 | 0.8571 | |
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| 0.5111 | 29.0 | 29 | 0.7062 | 0.8571 | |
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| 0.5111 | 30.0 | 30 | 0.7056 | 0.8571 | |
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| 0.5111 | 31.0 | 31 | 0.7050 | 0.8571 | |
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| 0.5111 | 32.0 | 32 | 0.7050 | 0.8571 | |
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| 0.5111 | 33.0 | 33 | 0.7031 | 0.8571 | |
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| 0.5111 | 34.0 | 34 | 0.7016 | 0.8571 | |
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| 0.5111 | 35.0 | 35 | 0.6996 | 0.8571 | |
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| 0.5111 | 36.0 | 36 | 0.6971 | 0.8571 | |
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| 0.5111 | 37.0 | 37 | 0.6953 | 0.8571 | |
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| 0.5111 | 38.0 | 38 | 0.6939 | 0.8571 | |
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| 0.5111 | 39.0 | 39 | 0.6938 | 0.8571 | |
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| 0.1719 | 40.0 | 40 | 0.6936 | 0.8571 | |
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### Framework versions |
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- Transformers 4.21.2 |
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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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