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--- |
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license: other |
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base_model: apple/mobilevitv2-1.0-imagenet1k-256 |
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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: mobilevit-trained-task3 |
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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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# mobilevit-trained-task3 |
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This model is a fine-tuned version of [apple/mobilevitv2-1.0-imagenet1k-256](https://huggingface.co/apple/mobilevitv2-1.0-imagenet1k-256) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1371 |
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- Accuracy: 0.9670 |
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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: 0.001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 20 |
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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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| 0.6753 | 0.99 | 126 | 0.8382 | 0.7376 | |
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| 0.6882 | 2.0 | 253 | 0.6129 | 0.7874 | |
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| 0.4068 | 3.0 | 380 | 0.3532 | 0.8876 | |
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| 0.3587 | 4.0 | 507 | 0.4896 | 0.8622 | |
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| 0.3013 | 4.99 | 633 | 0.2656 | 0.9078 | |
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| 0.2777 | 6.0 | 760 | 0.1679 | 0.9472 | |
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| 0.2093 | 7.0 | 887 | 0.2264 | 0.9302 | |
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| 0.1866 | 8.0 | 1014 | 0.2245 | 0.9263 | |
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| 0.1896 | 8.99 | 1140 | 0.2252 | 0.9333 | |
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| 0.1059 | 10.0 | 1267 | 0.1544 | 0.9528 | |
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| 0.1072 | 11.0 | 1394 | 0.2232 | 0.9391 | |
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| 0.1121 | 12.0 | 1521 | 0.1723 | 0.9467 | |
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| 0.103 | 12.99 | 1647 | 0.1750 | 0.9530 | |
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| 0.071 | 14.0 | 1774 | 0.1713 | 0.9541 | |
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| 0.0276 | 15.0 | 1901 | 0.1384 | 0.9631 | |
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| 0.0279 | 16.0 | 2028 | 0.1575 | 0.9607 | |
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| 0.0396 | 16.99 | 2154 | 0.1579 | 0.9604 | |
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| 0.0129 | 18.0 | 2281 | 0.1389 | 0.9674 | |
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| 0.0031 | 19.0 | 2408 | 0.1315 | 0.9689 | |
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| 0.0074 | 19.88 | 2520 | 0.1371 | 0.9670 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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