| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| model-index: | |
| - name: vit-fire-detection | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # vit-fire-detection | |
| 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. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0259 | |
| - Precision: 0.9947 | |
| - Recall: 0.9947 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 0.0002 | |
| - train_batch_size: 32 | |
| - eval_batch_size: 32 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 100 | |
| - num_epochs: 2 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| | |
| | 0.1186 | 1.0 | 190 | 0.0757 | 0.9789 | 0.9775 | | |
| | 0.0392 | 2.0 | 380 | 0.0259 | 0.9947 | 0.9947 | | |
| ### Framework versions | |
| - Transformers 4.25.1 | |
| - Pytorch 1.14.0.dev20221111 | |
| - Datasets 2.8.0 | |
| - Tokenizers 0.12.1 | |