metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: vit-fire-detection
results: []
vit-fire-detection
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0103
- Precision: 0.9987
- Recall: 0.9987
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall |
|---|---|---|---|---|---|
| 0.0797 | 1.0 | 190 | 0.0811 | 0.9789 | 0.9775 |
| 0.0536 | 2.0 | 380 | 0.0205 | 0.9947 | 0.9947 |
| 0.0374 | 3.0 | 570 | 0.0283 | 0.9922 | 0.9921 |
| 0.0209 | 4.0 | 760 | 0.0046 | 1.0 | 1.0 |
| 0.0104 | 5.0 | 950 | 0.0128 | 0.9960 | 0.9960 |
| 0.0159 | 6.0 | 1140 | 0.0152 | 0.9947 | 0.9947 |
| 0.0119 | 7.0 | 1330 | 0.0084 | 0.9974 | 0.9974 |
| 0.0044 | 8.0 | 1520 | 0.0111 | 0.9987 | 0.9987 |
| 0.0077 | 9.0 | 1710 | 0.0094 | 0.9987 | 0.9987 |
| 0.0106 | 10.0 | 1900 | 0.0103 | 0.9987 | 0.9987 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0