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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: 0.9767441860465116 |
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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: 0.1403 |
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- Accuracy: 0.9767 |
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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 | 3 | 0.1491 | 0.9535 | |
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| No log | 2.0 | 6 | 0.1462 | 0.9535 | |
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| No log | 3.0 | 9 | 0.1403 | 0.9767 | |
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| No log | 4.0 | 12 | 0.1431 | 0.9767 | |
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| No log | 5.0 | 15 | 0.1761 | 0.9535 | |
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| No log | 6.0 | 18 | 0.1930 | 0.9535 | |
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| 0.2637 | 7.0 | 21 | 0.1677 | 0.9535 | |
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| 0.2637 | 8.0 | 24 | 0.1835 | 0.9767 | |
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| 0.2637 | 9.0 | 27 | 0.1804 | 0.9535 | |
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| 0.2637 | 10.0 | 30 | 0.1856 | 0.9535 | |
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| 0.2637 | 11.0 | 33 | 0.1719 | 0.9535 | |
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| 0.2637 | 12.0 | 36 | 0.1680 | 0.9535 | |
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| 0.2637 | 13.0 | 39 | 0.1571 | 0.9535 | |
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| 0.1687 | 14.0 | 42 | 0.1333 | 0.9535 | |
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| 0.1687 | 15.0 | 45 | 0.1285 | 0.9535 | |
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| 0.1687 | 16.0 | 48 | 0.1293 | 0.9535 | |
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| 0.1687 | 17.0 | 51 | 0.1208 | 0.9767 | |
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| 0.1687 | 18.0 | 54 | 0.1061 | 0.9767 | |
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| 0.1687 | 19.0 | 57 | 0.0978 | 0.9767 | |
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| 0.1435 | 20.0 | 60 | 0.1100 | 0.9535 | |
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| 0.1435 | 21.0 | 63 | 0.1205 | 0.9535 | |
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| 0.1435 | 22.0 | 66 | 0.1027 | 0.9767 | |
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| 0.1435 | 23.0 | 69 | 0.1041 | 0.9767 | |
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| 0.1435 | 24.0 | 72 | 0.1021 | 0.9767 | |
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| 0.1435 | 25.0 | 75 | 0.0974 | 0.9767 | |
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| 0.1435 | 26.0 | 78 | 0.1006 | 0.9535 | |
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| 0.1361 | 27.0 | 81 | 0.1011 | 0.9535 | |
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| 0.1361 | 28.0 | 84 | 0.0993 | 0.9767 | |
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| 0.1361 | 29.0 | 87 | 0.0951 | 0.9767 | |
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| 0.1361 | 30.0 | 90 | 0.0971 | 0.9767 | |
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| 0.1361 | 31.0 | 93 | 0.1036 | 0.9767 | |
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| 0.1361 | 32.0 | 96 | 0.1085 | 0.9767 | |
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| 0.1361 | 33.0 | 99 | 0.1099 | 0.9767 | |
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| 0.1221 | 34.0 | 102 | 0.1115 | 0.9767 | |
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| 0.1221 | 35.0 | 105 | 0.1133 | 0.9767 | |
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| 0.1221 | 36.0 | 108 | 0.1184 | 0.9535 | |
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| 0.1221 | 37.0 | 111 | 0.1215 | 0.9535 | |
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| 0.1221 | 38.0 | 114 | 0.1224 | 0.9535 | |
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| 0.1221 | 39.0 | 117 | 0.1222 | 0.9535 | |
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| 0.1135 | 40.0 | 120 | 0.1217 | 0.9535 | |
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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 2.5.1 |
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- Tokenizers 0.12.1 |
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