| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: swin-tiny-patch4-window7-224-med-device-classification |
| | 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. --> |
| |
|
| | # swin-tiny-patch4-window7-224-med-device-classification |
| |
|
| | This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2927 |
| | - Accuracy: 0.75 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 30 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 1.0 | 1 | 1.6093 | 0.5 | |
| | | No log | 2.0 | 2 | 1.6063 | 0.5 | |
| | | No log | 3.0 | 3 | 1.6063 | 0.5 | |
| | | No log | 4.0 | 4 | 1.6100 | 0.25 | |
| | | No log | 5.0 | 5 | 1.6100 | 0.25 | |
| | | No log | 6.0 | 6 | 1.6170 | 0.25 | |
| | | No log | 7.0 | 7 | 1.6170 | 0.25 | |
| | | No log | 8.0 | 8 | 1.5910 | 0.25 | |
| | | No log | 9.0 | 9 | 1.5910 | 0.25 | |
| | | 0.7949 | 10.0 | 10 | 1.5705 | 0.25 | |
| | | 0.7949 | 11.0 | 11 | 1.5705 | 0.25 | |
| | | 0.7949 | 12.0 | 12 | 1.5368 | 0.25 | |
| | | 0.7949 | 13.0 | 13 | 1.5368 | 0.25 | |
| | | 0.7949 | 14.0 | 14 | 1.4843 | 0.25 | |
| | | 0.7949 | 15.0 | 15 | 1.4843 | 0.25 | |
| | | 0.7949 | 16.0 | 16 | 1.4413 | 0.25 | |
| | | 0.7949 | 17.0 | 17 | 1.4413 | 0.25 | |
| | | 0.7949 | 18.0 | 18 | 1.4050 | 0.5 | |
| | | 0.7949 | 19.0 | 19 | 1.4050 | 0.5 | |
| | | 0.6509 | 20.0 | 20 | 1.3670 | 0.5 | |
| | | 0.6509 | 21.0 | 21 | 1.3670 | 0.5 | |
| | | 0.6509 | 22.0 | 22 | 1.3404 | 0.5 | |
| | | 0.6509 | 23.0 | 23 | 1.3404 | 0.5 | |
| | | 0.6509 | 24.0 | 24 | 1.3212 | 0.5 | |
| | | 0.6509 | 25.0 | 25 | 1.3212 | 0.5 | |
| | | 0.6509 | 26.0 | 26 | 1.3087 | 0.5 | |
| | | 0.6509 | 27.0 | 27 | 1.3087 | 0.5 | |
| | | 0.6509 | 28.0 | 28 | 1.2969 | 0.75 | |
| | | 0.6509 | 29.0 | 29 | 1.2969 | 0.75 | |
| | | 0.5774 | 30.0 | 30 | 1.2927 | 0.75 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.0 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.13.3 |
| |
|
