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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: 0.9714285714285714 |
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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: 0.1192 |
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- Accuracy: 0.9714 |
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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: 60 |
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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 | 5 | 1.9402 | 0.1286 | |
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| No log | 2.0 | 10 | 1.8379 | 0.2429 | |
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| No log | 3.0 | 15 | 1.6960 | 0.4 | |
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| 1.7795 | 4.0 | 20 | 1.4423 | 0.5143 | |
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| 1.7795 | 5.0 | 25 | 1.1295 | 0.6857 | |
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| 1.7795 | 6.0 | 30 | 0.8280 | 0.7286 | |
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| 1.7795 | 7.0 | 35 | 0.5572 | 0.8429 | |
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| 1.0588 | 8.0 | 40 | 0.3855 | 0.9286 | |
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| 1.0588 | 9.0 | 45 | 0.3107 | 0.9143 | |
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| 1.0588 | 10.0 | 50 | 0.2564 | 0.9286 | |
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| 1.0588 | 11.0 | 55 | 0.2050 | 0.9286 | |
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| 0.591 | 12.0 | 60 | 0.1900 | 0.9571 | |
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| 0.591 | 13.0 | 65 | 0.1720 | 0.9286 | |
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| 0.591 | 14.0 | 70 | 0.1881 | 0.9143 | |
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| 0.591 | 15.0 | 75 | 0.1789 | 0.9429 | |
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| 0.4609 | 16.0 | 80 | 0.1999 | 0.9143 | |
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| 0.4609 | 17.0 | 85 | 0.1492 | 0.9286 | |
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| 0.4609 | 18.0 | 90 | 0.1648 | 0.9286 | |
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| 0.4609 | 19.0 | 95 | 0.1195 | 0.9571 | |
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| 0.3941 | 20.0 | 100 | 0.1395 | 0.9286 | |
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| 0.3941 | 21.0 | 105 | 0.1476 | 0.9286 | |
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| 0.3941 | 22.0 | 110 | 0.1113 | 0.9571 | |
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| 0.3941 | 23.0 | 115 | 0.1328 | 0.9571 | |
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| 0.3475 | 24.0 | 120 | 0.1192 | 0.9714 | |
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| 0.3475 | 25.0 | 125 | 0.1200 | 0.9571 | |
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| 0.3475 | 26.0 | 130 | 0.1360 | 0.9714 | |
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| 0.3475 | 27.0 | 135 | 0.1425 | 0.9429 | |
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| 0.3542 | 28.0 | 140 | 0.1103 | 0.9571 | |
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| 0.3542 | 29.0 | 145 | 0.1244 | 0.9429 | |
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| 0.3542 | 30.0 | 150 | 0.1176 | 0.9571 | |
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| 0.3542 | 31.0 | 155 | 0.1028 | 0.9571 | |
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| 0.317 | 32.0 | 160 | 0.1084 | 0.9571 | |
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| 0.317 | 33.0 | 165 | 0.1269 | 0.9571 | |
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| 0.317 | 34.0 | 170 | 0.1295 | 0.9429 | |
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| 0.317 | 35.0 | 175 | 0.1245 | 0.9571 | |
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| 0.2947 | 36.0 | 180 | 0.1315 | 0.9429 | |
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| 0.2947 | 37.0 | 185 | 0.1313 | 0.9571 | |
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| 0.2947 | 38.0 | 190 | 0.1421 | 0.9429 | |
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| 0.2947 | 39.0 | 195 | 0.1440 | 0.9571 | |
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| 0.3124 | 40.0 | 200 | 0.1339 | 0.9571 | |
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| 0.3124 | 41.0 | 205 | 0.1553 | 0.9429 | |
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| 0.3124 | 42.0 | 210 | 0.1547 | 0.9429 | |
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| 0.3124 | 43.0 | 215 | 0.1316 | 0.9571 | |
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| 0.2843 | 44.0 | 220 | 0.1287 | 0.9571 | |
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| 0.2843 | 45.0 | 225 | 0.1308 | 0.9571 | |
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| 0.2843 | 46.0 | 230 | 0.1401 | 0.9571 | |
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| 0.2843 | 47.0 | 235 | 0.1186 | 0.9571 | |
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| 0.2655 | 48.0 | 240 | 0.1057 | 0.9571 | |
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| 0.2655 | 49.0 | 245 | 0.1203 | 0.9571 | |
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| 0.2655 | 50.0 | 250 | 0.1374 | 0.9571 | |
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| 0.2655 | 51.0 | 255 | 0.1361 | 0.9571 | |
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| 0.26 | 52.0 | 260 | 0.1198 | 0.9571 | |
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| 0.26 | 53.0 | 265 | 0.1175 | 0.9571 | |
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| 0.26 | 54.0 | 270 | 0.1313 | 0.9571 | |
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| 0.26 | 55.0 | 275 | 0.1398 | 0.9429 | |
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| 0.2601 | 56.0 | 280 | 0.1354 | 0.9571 | |
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| 0.2601 | 57.0 | 285 | 0.1271 | 0.9571 | |
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| 0.2601 | 58.0 | 290 | 0.1242 | 0.9571 | |
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| 0.2601 | 59.0 | 295 | 0.1233 | 0.9571 | |
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| 0.2562 | 60.0 | 300 | 0.1235 | 0.9571 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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