license: apache-2.0 | |
tags: | |
- generated_from_trainer | |
metrics: | |
- precision | |
- recall | |
model-index: | |
- name: vit-fire-detection | |
results: [] | |
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# 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 | |