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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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metrics: |
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- precision |
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- recall |
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model-index: |
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- name: vit-fire-detection |
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results: [] |
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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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# vit-fire-detection |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0189 |
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- Precision: 0.9974 |
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- Recall: 0.9974 |
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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: 0.0002 |
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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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- 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_steps: 100 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| 0.1023 | 1.0 | 190 | 0.0528 | 0.9829 | 0.9828 | |
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| 0.058 | 2.0 | 380 | 0.0375 | 0.9896 | 0.9894 | |
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| 0.038 | 3.0 | 570 | 0.0359 | 0.9909 | 0.9907 | |
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| 0.0283 | 4.0 | 760 | 0.0467 | 0.9861 | 0.9854 | |
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| 0.0326 | 5.0 | 950 | 0.0222 | 0.9934 | 0.9934 | |
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| 0.0257 | 6.0 | 1140 | 0.0249 | 0.9934 | 0.9934 | |
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| 0.0259 | 7.0 | 1330 | 0.0296 | 0.9921 | 0.9921 | |
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| 0.0171 | 8.0 | 1520 | 0.0239 | 0.9948 | 0.9947 | |
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| 0.0211 | 9.0 | 1710 | 0.0190 | 0.9974 | 0.9974 | |
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| 0.0054 | 10.0 | 1900 | 0.0189 | 0.9974 | 0.9974 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.14.0.dev20221111 |
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- Datasets 2.8.0 |
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- Tokenizers 0.12.1 |
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