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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft |
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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: Train-Augmentation-V2-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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# Train-Augmentation-V2-swinv2-base |
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This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9822 |
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- Accuracy: 0.8459 |
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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: 15 |
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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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| 0.5894 | 0.99 | 109 | 0.7123 | 0.7481 | |
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| 0.2772 | 2.0 | 219 | 0.6394 | 0.7970 | |
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| 0.1863 | 3.0 | 329 | 0.7819 | 0.7669 | |
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| 0.0925 | 4.0 | 439 | 0.7062 | 0.8083 | |
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| 0.0461 | 4.99 | 548 | 0.8637 | 0.8120 | |
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| 0.0427 | 6.0 | 658 | 0.9080 | 0.7970 | |
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| 0.043 | 7.0 | 768 | 1.0747 | 0.8045 | |
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| 0.0074 | 8.0 | 878 | 0.9019 | 0.8421 | |
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| 0.0169 | 8.99 | 987 | 0.9099 | 0.8459 | |
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| 0.015 | 10.0 | 1097 | 0.9512 | 0.8647 | |
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| 0.0022 | 11.0 | 1207 | 1.0051 | 0.8609 | |
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| 0.0081 | 12.0 | 1317 | 1.0061 | 0.8308 | |
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| 0.0013 | 12.99 | 1426 | 0.9844 | 0.8534 | |
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| 0.0037 | 14.0 | 1536 | 0.9864 | 0.8459 | |
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| 0.0002 | 14.9 | 1635 | 0.9822 | 0.8459 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.2 |
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