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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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- image_folder |
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metrics: |
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- accuracy |
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model-index: |
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- name: violation-classification-bantai-vit-v100ep |
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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: image_folder |
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type: image_folder |
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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: 0.9157343919162757 |
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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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# violation-classification-bantai-vit-v100ep |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2557 |
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- Accuracy: 0.9157 |
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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: 100 |
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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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| 0.2811 | 1.0 | 101 | 0.2855 | 0.9027 | |
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| 0.2382 | 2.0 | 202 | 0.2763 | 0.9085 | |
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| 0.2361 | 3.0 | 303 | 0.2605 | 0.9109 | |
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| 0.196 | 4.0 | 404 | 0.2652 | 0.9110 | |
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| 0.1395 | 5.0 | 505 | 0.2648 | 0.9134 | |
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| 0.155 | 6.0 | 606 | 0.2656 | 0.9152 | |
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| 0.1422 | 7.0 | 707 | 0.2607 | 0.9141 | |
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| 0.1511 | 8.0 | 808 | 0.2557 | 0.9157 | |
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| 0.1938 | 9.0 | 909 | 0.2679 | 0.9049 | |
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| 0.2094 | 10.0 | 1010 | 0.2392 | 0.9137 | |
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| 0.1835 | 11.0 | 1111 | 0.2400 | 0.9156 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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