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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-base-patch4-window12-192-22k |
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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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model-index: |
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- name: 0.50-200Train-100Test-swinv2-base |
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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 |
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should probably proofread and complete it, then remove this comment. --> |
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# 0.50-200Train-100Test-swinv2-base |
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This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1459 |
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- Accuracy: 0.8183 |
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## Model description |
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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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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 17 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| 1.7214 | 0.9931 | 36 | 1.0786 | 0.6515 | |
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| 0.6184 | 1.9862 | 72 | 0.7491 | 0.7651 | |
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| 0.357 | 2.9793 | 108 | 0.7632 | 0.7764 | |
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| 0.2085 | 4.0 | 145 | 0.8125 | 0.7860 | |
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| 0.1343 | 4.9931 | 181 | 0.7920 | 0.7974 | |
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| 0.0641 | 5.9862 | 217 | 0.8851 | 0.7860 | |
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| 0.0515 | 6.9793 | 253 | 1.0784 | 0.7817 | |
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| 0.041 | 8.0 | 290 | 1.0600 | 0.7965 | |
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| 0.0338 | 8.9931 | 326 | 1.0860 | 0.8131 | |
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| 0.013 | 9.9862 | 362 | 1.0956 | 0.8148 | |
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| 0.016 | 10.9793 | 398 | 1.2115 | 0.7991 | |
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| 0.0154 | 12.0 | 435 | 1.1470 | 0.8105 | |
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| 0.011 | 12.9931 | 471 | 1.1045 | 0.8105 | |
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| 0.0027 | 13.9862 | 507 | 1.1310 | 0.8096 | |
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| 0.0042 | 14.9793 | 543 | 1.1808 | 0.8227 | |
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| 0.0016 | 16.0 | 580 | 1.1575 | 0.8157 | |
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| 0.0007 | 16.8828 | 612 | 1.1459 | 0.8183 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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