| | --- |
| | license: apache-2.0 |
| | base_model: microsoft/swinv2-tiny-patch4-window16-256 |
| | tags: |
| | - image-classification |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: save-model-final-fork |
| | 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. --> |
| |
|
| | # save-model-final-fork |
| |
|
| | This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window16-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window16-256) on the jbarat/plant_species dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0002 |
| | - Accuracy: 1.0 |
| | |
| | ## 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: 0.0003 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 21 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Accuracy | Validation Loss | |
| | |:-------------:|:-----:|:----:|:--------:|:---------------:| |
| | | No log | 1.0 | 10 | 0.725 | 0.7459 | |
| | | No log | 2.0 | 20 | 0.875 | 0.5996 | |
| | | No log | 3.0 | 30 | 0.7375 | 0.8398 | |
| | | No log | 4.0 | 40 | 0.8125 | 0.6444 | |
| | | No log | 5.0 | 50 | 0.8375 | 0.6891 | |
| | | No log | 6.0 | 60 | 0.825 | 0.6675 | |
| | | No log | 7.0 | 70 | 0.8375 | 0.7300 | |
| | | No log | 8.0 | 80 | 0.85 | 0.8635 | |
| | | No log | 9.0 | 90 | 0.95 | 0.3333 | |
| | | 0.1657 | 10.0 | 100 | 0.9375 | 0.2634 | |
| | | 0.1657 | 11.0 | 110 | 0.9375 | 0.3821 | |
| | | 0.1657 | 12.0 | 120 | 0.9625 | 0.2343 | |
| | | 0.1657 | 13.0 | 130 | 0.9375 | 0.3103 | |
| | | 0.1657 | 14.0 | 140 | 0.95 | 0.3481 | |
| | | 0.1657 | 15.0 | 150 | 0.9625 | 0.2419 | |
| | | 0.1657 | 16.0 | 160 | 0.9375 | 0.2408 | |
| | | 0.1657 | 17.0 | 170 | 0.95 | 0.3202 | |
| | | 0.1657 | 18.0 | 180 | 0.9125 | 0.4016 | |
| | | 0.1657 | 19.0 | 190 | 0.925 | 0.3918 | |
| | | 0.0254 | 20.0 | 200 | 0.9375 | 0.3874 | |
| | | 0.0254 | 21.0 | 210 | 0.0006 | 1.0 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.39.3 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
