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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-base-patch4-window12-384 |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: 10-swin-base-patch4-window12-384-finetuned-spiderTraining20-500 |
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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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# 10-swin-base-patch4-window12-384-finetuned-spiderTraining20-500 |
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This model is a fine-tuned version of [microsoft/swin-base-patch4-window12-384](https://huggingface.co/microsoft/swin-base-patch4-window12-384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3023 |
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- Accuracy: 0.9339 |
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- Precision: 0.9335 |
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- Recall: 0.9314 |
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- F1: 0.9313 |
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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: 0.0005 |
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- train_batch_size: 25 |
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- eval_batch_size: 25 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 100 |
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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 | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.786 | 1.0 | 80 | 0.6341 | 0.7918 | 0.8135 | 0.7860 | 0.7830 | |
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| 0.6519 | 2.0 | 160 | 0.6522 | 0.7958 | 0.8177 | 0.7913 | 0.7840 | |
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| 0.6352 | 3.0 | 240 | 0.5289 | 0.8328 | 0.8473 | 0.8255 | 0.8258 | |
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| 0.4922 | 4.0 | 320 | 0.5681 | 0.8448 | 0.8680 | 0.8386 | 0.8396 | |
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| 0.3959 | 5.0 | 400 | 0.3896 | 0.8799 | 0.8816 | 0.8772 | 0.8755 | |
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| 0.3277 | 6.0 | 480 | 0.3588 | 0.9119 | 0.9073 | 0.9104 | 0.9080 | |
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| 0.284 | 7.0 | 560 | 0.3355 | 0.9099 | 0.9126 | 0.9066 | 0.9058 | |
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| 0.2075 | 8.0 | 640 | 0.2876 | 0.9289 | 0.9271 | 0.9287 | 0.9269 | |
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| 0.1751 | 9.0 | 720 | 0.2871 | 0.9349 | 0.9337 | 0.9320 | 0.9321 | |
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| 0.1923 | 10.0 | 800 | 0.3023 | 0.9339 | 0.9335 | 0.9314 | 0.9313 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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