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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: 0.9259259259259259 |
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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: 0.2419 |
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- Accuracy: 0.9259 |
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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 | 0.8 | 3 | 1.8673 | 0.2222 | |
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| No log | 1.8 | 6 | 1.7421 | 0.2593 | |
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| No log | 2.8 | 9 | 1.5910 | 0.4259 | |
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| No log | 3.8 | 12 | 1.4371 | 0.5 | |
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| No log | 4.8 | 15 | 1.2871 | 0.5741 | |
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| No log | 5.8 | 18 | 1.1511 | 0.5741 | |
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| 1.8164 | 6.8 | 21 | 0.9363 | 0.7222 | |
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| 1.8164 | 7.8 | 24 | 0.7903 | 0.7778 | |
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| 1.8164 | 8.8 | 27 | 0.6839 | 0.7593 | |
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| 1.8164 | 9.8 | 30 | 0.5661 | 0.7778 | |
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| 1.8164 | 10.8 | 33 | 0.4638 | 0.8519 | |
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| 1.8164 | 11.8 | 36 | 0.4015 | 0.8704 | |
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| 1.8164 | 12.8 | 39 | 0.3809 | 0.8704 | |
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| 0.8525 | 13.8 | 42 | 0.3214 | 0.9074 | |
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| 0.8525 | 14.8 | 45 | 0.3114 | 0.8704 | |
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| 0.8525 | 15.8 | 48 | 0.3026 | 0.8889 | |
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| 0.8525 | 16.8 | 51 | 0.2970 | 0.8889 | |
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| 0.8525 | 17.8 | 54 | 0.2597 | 0.8889 | |
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| 0.8525 | 18.8 | 57 | 0.2792 | 0.8889 | |
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| 0.4831 | 19.8 | 60 | 0.3209 | 0.8704 | |
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| 0.4831 | 20.8 | 63 | 0.2929 | 0.9074 | |
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| 0.4831 | 21.8 | 66 | 0.2419 | 0.9259 | |
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| 0.4831 | 22.8 | 69 | 0.2496 | 0.9074 | |
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| 0.4831 | 23.8 | 72 | 0.2953 | 0.9074 | |
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| 0.4831 | 24.8 | 75 | 0.3094 | 0.8889 | |
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| 0.4831 | 25.8 | 78 | 0.2792 | 0.9259 | |
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| 0.3889 | 26.8 | 81 | 0.2522 | 0.9259 | |
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| 0.3889 | 27.8 | 84 | 0.2451 | 0.9259 | |
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| 0.3889 | 28.8 | 87 | 0.2541 | 0.9074 | |
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| 0.3889 | 29.8 | 90 | 0.2718 | 0.9074 | |
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| 0.3889 | 30.8 | 93 | 0.2738 | 0.9074 | |
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| 0.3889 | 31.8 | 96 | 0.2639 | 0.9259 | |
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| 0.3889 | 32.8 | 99 | 0.2561 | 0.9259 | |
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| 0.3407 | 33.8 | 102 | 0.2497 | 0.9259 | |
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| 0.3407 | 34.8 | 105 | 0.2501 | 0.9259 | |
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| 0.3407 | 35.8 | 108 | 0.2455 | 0.9259 | |
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| 0.3407 | 36.8 | 111 | 0.2381 | 0.9259 | |
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| 0.3407 | 37.8 | 114 | 0.2340 | 0.9259 | |
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| 0.3407 | 38.8 | 117 | 0.2321 | 0.9259 | |
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| 0.3112 | 39.8 | 120 | 0.2315 | 0.9259 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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