| | ---
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| | license: apache-2.0
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| | base_model: microsoft/swinv2-tiny-patch4-window8-256
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| | tags:
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| | - generated_from_trainer
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| | datasets:
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| | - imagefolder
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| | metrics:
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| | - accuracy
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| | model-index:
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| | - name: SW2-RHS-DA
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| | results:
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| | - task:
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| | name: Image Classification
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| | type: image-classification
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| | dataset:
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| | name: imagefolder
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| | type: imagefolder
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| | config: default
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| | split: validation
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| | args: default
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| | metrics:
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| | - name: Accuracy
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| | type: accuracy
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| | value: 0.616822429906542
|
| | ---
|
| |
|
| | <!-- 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. -->
|
| |
|
| | # SW2-RHS-DA
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| |
|
| | This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 2.1002
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| | - Accuracy: 0.6168
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| |
|
| | ## Model description
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| |
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| | More information needed
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| |
|
| | ## Intended uses & limitations
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| |
|
| | More information needed
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| |
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| | ## Training and evaluation data
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| |
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| | More information needed
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| |
|
| | ## Training procedure
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| |
|
| | ### Training hyperparameters
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| |
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| | The following hyperparameters were used during training:
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| | - learning_rate: 4e-05
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| | - train_batch_size: 16
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| | - eval_batch_size: 16
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| | - seed: 42
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| | - gradient_accumulation_steps: 4
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| | - total_train_batch_size: 64
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| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| | - lr_scheduler_type: linear
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| | - num_epochs: 40
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| |
|
| | ### Training results
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| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| | | 1.302 | 0.98 | 22 | 2.8474 | 0.4112 |
|
| | | 0.6224 | 2.0 | 45 | 1.4650 | 0.4112 |
|
| | | 0.3905 | 2.98 | 67 | 1.4865 | 0.4112 |
|
| | | 0.1416 | 4.0 | 90 | 0.9453 | 0.5981 |
|
| | | 0.1116 | 4.98 | 112 | 0.9801 | 0.5514 |
|
| | | 0.0866 | 6.0 | 135 | 1.5201 | 0.6075 |
|
| | | 0.0579 | 6.98 | 157 | 1.7234 | 0.5981 |
|
| | | 0.0667 | 8.0 | 180 | 1.9649 | 0.5981 |
|
| | | 0.0664 | 8.98 | 202 | 1.9505 | 0.5981 |
|
| | | 0.0742 | 10.0 | 225 | 1.9448 | 0.5981 |
|
| | | 0.0558 | 10.98 | 247 | 1.9545 | 0.5981 |
|
| | | 0.0475 | 12.0 | 270 | 2.1516 | 0.5888 |
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| | | 0.114 | 12.98 | 292 | 2.1002 | 0.6168 |
|
| | | 0.051 | 14.0 | 315 | 2.2643 | 0.5981 |
|
| | | 0.0318 | 14.98 | 337 | 2.3468 | 0.5981 |
|
| | | 0.0673 | 16.0 | 360 | 2.3341 | 0.6075 |
|
| | | 0.0566 | 16.98 | 382 | 2.3191 | 0.6075 |
|
| | | 0.0543 | 18.0 | 405 | 2.2807 | 0.6168 |
|
| | | 0.0458 | 18.98 | 427 | 2.2148 | 0.6168 |
|
| | | 0.0421 | 20.0 | 450 | 2.5468 | 0.5888 |
|
| | | 0.0139 | 20.98 | 472 | 2.2408 | 0.6168 |
|
| | | 0.012 | 22.0 | 495 | 2.5689 | 0.5888 |
|
| | | 0.017 | 22.98 | 517 | 2.5485 | 0.6168 |
|
| | | 0.0529 | 24.0 | 540 | 2.6746 | 0.6075 |
|
| | | 0.0414 | 24.98 | 562 | 2.7693 | 0.5888 |
|
| | | 0.0158 | 26.0 | 585 | 2.7447 | 0.5888 |
|
| | | 0.0205 | 26.98 | 607 | 2.8566 | 0.5888 |
|
| | | 0.0205 | 28.0 | 630 | 2.8469 | 0.5888 |
|
| | | 0.006 | 28.98 | 652 | 2.9508 | 0.5888 |
|
| | | 0.0061 | 30.0 | 675 | 3.0560 | 0.5888 |
|
| | | 0.0227 | 30.98 | 697 | 3.0431 | 0.5888 |
|
| | | 0.034 | 32.0 | 720 | 3.0497 | 0.5888 |
|
| | | 0.0039 | 32.98 | 742 | 3.0936 | 0.5888 |
|
| | | 0.0031 | 34.0 | 765 | 3.1158 | 0.5888 |
|
| | | 0.0118 | 34.98 | 787 | 3.1093 | 0.5888 |
|
| | | 0.0045 | 36.0 | 810 | 3.0885 | 0.5888 |
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| | | 0.0168 | 36.98 | 832 | 3.0814 | 0.5888 |
|
| | | 0.0071 | 38.0 | 855 | 3.0733 | 0.5888 |
|
| | | 0.0238 | 38.98 | 877 | 3.0825 | 0.5888 |
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| | | 0.0072 | 39.11 | 880 | 3.0828 | 0.5888 |
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| |
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| |
|
| | ### Framework versions
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| |
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| | - Transformers 4.36.2
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| | - Pytorch 2.1.2+cu118
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| | - Datasets 2.16.1
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| | - Tokenizers 0.15.0
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| | |
