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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: Balanced-No-Augmentation-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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# Balanced-No-Augmentation-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: 3.6109 |
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- Accuracy: 0.5692 |
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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: 16 |
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- total_train_batch_size: 256 |
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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: 10 |
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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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| 2.2985 | 0.98 | 11 | 1.4531 | 0.4822 | |
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| 0.9081 | 1.97 | 22 | 1.5086 | 0.5731 | |
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| 0.4604 | 2.95 | 33 | 1.9810 | 0.5692 | |
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| 0.2255 | 3.93 | 44 | 3.0618 | 0.5415 | |
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| 0.1339 | 4.92 | 55 | 2.8634 | 0.5613 | |
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| 0.0883 | 5.99 | 67 | 3.0244 | 0.5652 | |
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| 0.0605 | 6.97 | 78 | 3.5175 | 0.5573 | |
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| 0.0506 | 7.96 | 89 | 3.4068 | 0.5850 | |
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| 0.0272 | 8.94 | 100 | 3.6996 | 0.5573 | |
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| 0.0262 | 9.83 | 110 | 3.6109 | 0.5692 | |
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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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