hoarding-detection-yolos
This model is a fine-tuned version of hustvl/yolos-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0530
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3213 | 1.0 | 346 | 1.4447 |
| 1.216 | 2.0 | 692 | 1.3241 |
| 1.2263 | 3.0 | 1038 | 1.3540 |
| 1.021 | 4.0 | 1384 | 1.2100 |
| 0.9946 | 5.0 | 1730 | 1.1664 |
| 0.9623 | 6.0 | 2076 | 1.1285 |
| 0.8784 | 7.0 | 2422 | 1.1428 |
| 0.7868 | 8.0 | 2768 | 1.1187 |
| 0.7513 | 9.0 | 3114 | 1.0768 |
| 0.7086 | 10.0 | 3460 | 1.0530 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.6.0+cu124
- Datasets 4.5.0
- Tokenizers 0.22.1