| | ---
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| | library_name: transformers
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| | license: apache-2.0
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| | base_model: microsoft/swinv2-base-patch4-window16-256
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| | tags:
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| | - generated_from_trainer
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| | metrics:
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| | - accuracy
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| | - f1
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| | model-index:
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| | - name: swinv2-plantclef
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| | results: []
|
| | ---
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| |
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| | <!-- 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. -->
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| |
|
| | # swinv2-plantclef
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| |
|
| | This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window16-256](https://huggingface.co/microsoft/swinv2-base-patch4-window16-256) on an unknown dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 1.0548
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| | - Accuracy: 0.8199
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| | - F1: 0.8190
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| |
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| | ## Model description
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| |
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| | More information needed
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| |
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| | ## Intended uses & limitations
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| |
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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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| |
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| | ## Training procedure
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| |
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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: 5e-05
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| | - train_batch_size: 32
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| | - eval_batch_size: 32
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| | - seed: 42
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| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| | - lr_scheduler_type: linear
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| | - num_epochs: 16
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| | - mixed_precision_training: Native AMP
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| |
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| | ### Training results
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| |
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| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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| | | 1.1414 | 1.0 | 897 | 0.9819 | 0.7171 | 0.7046 |
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| | | 0.654 | 2.0 | 1794 | 0.7608 | 0.7694 | 0.7688 |
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| | | 0.394 | 3.0 | 2691 | 0.7461 | 0.7795 | 0.7767 |
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| | | 0.2437 | 4.0 | 3588 | 0.7369 | 0.7917 | 0.7908 |
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| | | 0.1428 | 5.0 | 4485 | 0.7939 | 0.7945 | 0.7929 |
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| | | 0.0878 | 6.0 | 5382 | 0.8352 | 0.7958 | 0.7950 |
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| | | 0.0621 | 7.0 | 6279 | 0.8802 | 0.7945 | 0.7928 |
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| | | 0.0353 | 8.0 | 7176 | 0.9028 | 0.8011 | 0.8005 |
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| | | 0.0241 | 9.0 | 8073 | 0.9592 | 0.8043 | 0.8045 |
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| | | 0.0241 | 10.0 | 8970 | 1.0075 | 0.8068 | 0.8047 |
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| | | 0.0129 | 11.0 | 9867 | 1.0254 | 0.8127 | 0.8120 |
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| | | 0.0058 | 12.0 | 10764 | 1.0340 | 0.8162 | 0.8151 |
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| | | 0.007 | 13.0 | 11661 | 1.0661 | 0.8165 | 0.8159 |
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| | | 0.0052 | 14.0 | 12558 | 1.0533 | 0.8168 | 0.8166 |
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| | | 0.0049 | 15.0 | 13455 | 1.0660 | 0.8174 | 0.8164 |
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| | | 0.015 | 16.0 | 14352 | 1.0548 | 0.8199 | 0.8190 |
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| |
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| |
|
| | ### Framework versions
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| |
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| | - Transformers 4.46.2
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| | - Pytorch 2.5.0
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| | - Datasets 3.1.0
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| | - Tokenizers 0.20.1
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| |
|
