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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: 0.9555555555555556 |
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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 [JEdward7777/delivery_truck_classification](https://huggingface.co/JEdward7777/delivery_truck_classification) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2060 |
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- Accuracy: 0.9556 |
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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 | 0.92 | 3 | 0.3269 | 0.9111 | |
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| No log | 1.92 | 6 | 0.2814 | 0.9333 | |
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| No log | 2.92 | 9 | 0.2625 | 0.9333 | |
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| No log | 3.92 | 12 | 0.2771 | 0.9333 | |
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| No log | 4.92 | 15 | 0.2419 | 0.9333 | |
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| No log | 5.92 | 18 | 0.2264 | 0.9111 | |
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| 0.3207 | 6.92 | 21 | 0.2530 | 0.9333 | |
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| 0.3207 | 7.92 | 24 | 0.2242 | 0.9333 | |
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| 0.3207 | 8.92 | 27 | 0.2060 | 0.9556 | |
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| 0.3207 | 9.92 | 30 | 0.1809 | 0.9556 | |
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| 0.3207 | 10.92 | 33 | 0.2070 | 0.9556 | |
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| 0.3207 | 11.92 | 36 | 0.1999 | 0.9556 | |
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| 0.3207 | 12.92 | 39 | 0.2013 | 0.9556 | |
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| 0.2066 | 13.92 | 42 | 0.2027 | 0.9556 | |
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| 0.2066 | 14.92 | 45 | 0.1809 | 0.9556 | |
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| 0.2066 | 15.92 | 48 | 0.1657 | 0.9556 | |
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| 0.2066 | 16.92 | 51 | 0.1728 | 0.9556 | |
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| 0.2066 | 17.92 | 54 | 0.2013 | 0.9556 | |
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| 0.2066 | 18.92 | 57 | 0.2226 | 0.9556 | |
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| 0.1894 | 19.92 | 60 | 0.2091 | 0.9556 | |
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| 0.1894 | 20.92 | 63 | 0.1940 | 0.9556 | |
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| 0.1894 | 21.92 | 66 | 0.1976 | 0.9556 | |
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| 0.1894 | 22.92 | 69 | 0.2232 | 0.9556 | |
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| 0.1894 | 23.92 | 72 | 0.2381 | 0.9556 | |
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| 0.1894 | 24.92 | 75 | 0.2405 | 0.9556 | |
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| 0.1894 | 25.92 | 78 | 0.2247 | 0.9556 | |
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| 0.1713 | 26.92 | 81 | 0.1895 | 0.9556 | |
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| 0.1713 | 27.92 | 84 | 0.1836 | 0.9556 | |
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| 0.1713 | 28.92 | 87 | 0.1985 | 0.9556 | |
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| 0.1713 | 29.92 | 90 | 0.2127 | 0.9556 | |
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| 0.1713 | 30.92 | 93 | 0.2098 | 0.9556 | |
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| 0.1713 | 31.92 | 96 | 0.2003 | 0.9556 | |
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| 0.1713 | 32.92 | 99 | 0.1849 | 0.9556 | |
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| 0.1428 | 33.92 | 102 | 0.1843 | 0.9556 | |
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| 0.1428 | 34.92 | 105 | 0.1900 | 0.9556 | |
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| 0.1428 | 35.92 | 108 | 0.1972 | 0.9556 | |
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| 0.1428 | 36.92 | 111 | 0.2023 | 0.9556 | |
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| 0.1428 | 37.92 | 114 | 0.2060 | 0.9556 | |
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| 0.1428 | 38.92 | 117 | 0.2093 | 0.9556 | |
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| 0.1443 | 39.92 | 120 | 0.2106 | 0.9556 | |
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### Framework versions |
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- Transformers 4.22.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.2 |
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- Tokenizers 0.12.1 |
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