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--- |
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license: apache-2.0 |
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base_model: microsoft/resnet-34 |
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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: resnet-fine_tuned |
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results: [] |
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datasets: |
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- Falah/Alzheimer_MRI |
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library_name: transformers |
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pipeline_tag: image-classification |
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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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# resnet-fine_tuned |
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This model is a fine-tuned version of [microsoft/resnet-34](https://huggingface.co./microsoft/resnet-34) on the Falah/Alzheimer_MRI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1983 |
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- Accuracy: 0.9219 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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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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| 0.9041 | 1.0 | 80 | 0.9659 | 0.5352 | |
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| 0.8743 | 2.0 | 160 | 0.9348 | 0.5797 | |
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| 0.7723 | 3.0 | 240 | 0.7793 | 0.6594 | |
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| 0.6864 | 4.0 | 320 | 0.6799 | 0.7031 | |
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| 0.5347 | 5.0 | 400 | 0.5596 | 0.7703 | |
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| 0.4282 | 6.0 | 480 | 0.5078 | 0.7766 | |
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| 0.4315 | 7.0 | 560 | 0.5455 | 0.7680 | |
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| 0.3747 | 8.0 | 640 | 0.4203 | 0.8266 | |
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| 0.2977 | 9.0 | 720 | 0.3926 | 0.8469 | |
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| 0.2252 | 10.0 | 800 | 0.3024 | 0.8742 | |
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| 0.2675 | 11.0 | 880 | 0.2731 | 0.8906 | |
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| 0.2136 | 12.0 | 960 | 0.3045 | 0.875 | |
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| 0.1998 | 13.0 | 1040 | 0.2370 | 0.9 | |
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| 0.2406 | 14.0 | 1120 | 0.2387 | 0.9086 | |
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| 0.1873 | 15.0 | 1200 | 0.1983 | 0.9219 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cpu |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
