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--- |
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license: other |
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base_model: apple/mobilevit-xx-small |
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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: KDRSSC_TinyViT2MobileViT-xx-small |
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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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# KDRSSC_TinyViT2MobileViT-xx-small |
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This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co./apple/mobilevit-xx-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8217 |
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- Accuracy: 0.8398 |
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- Precision: 0.8409 |
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- Recall: 0.8398 |
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- F1: 0.8365 |
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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: 0.0001 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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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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- 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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| 2.1113 | 1.0 | 148 | 1.7471 | 0.588 | 0.6313 | 0.588 | 0.5698 | |
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| 1.6003 | 2.0 | 296 | 1.3462 | 0.704 | 0.7133 | 0.704 | 0.6844 | |
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| 1.2989 | 3.0 | 444 | 1.1278 | 0.759 | 0.7716 | 0.759 | 0.7509 | |
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| 1.1115 | 4.0 | 592 | 0.9891 | 0.802 | 0.8022 | 0.802 | 0.7952 | |
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| 0.9978 | 5.0 | 740 | 0.9123 | 0.827 | 0.8413 | 0.827 | 0.8255 | |
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| 0.9274 | 6.0 | 888 | 0.8512 | 0.843 | 0.8445 | 0.843 | 0.8387 | |
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| 0.8748 | 7.0 | 1036 | 0.8210 | 0.842 | 0.8412 | 0.842 | 0.8373 | |
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| 0.8411 | 8.0 | 1184 | 0.7952 | 0.842 | 0.8398 | 0.842 | 0.8365 | |
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| 0.818 | 9.0 | 1332 | 0.7814 | 0.852 | 0.8574 | 0.852 | 0.8489 | |
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| 0.8081 | 10.0 | 1480 | 0.7796 | 0.853 | 0.8591 | 0.853 | 0.8487 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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