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--- |
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license: apache-2.0 |
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base_model: microsoft/resnet-50 |
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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-50-image-classification |
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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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# resnet-50-image-classification |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3093 |
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- Accuracy: 0.9408 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 101010 |
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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_steps: 2000 |
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- num_epochs: 40 |
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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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| No log | 1.0 | 338 | 2.2768 | 0.5172 | |
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| 2.2806 | 2.0 | 676 | 2.0111 | 0.6903 | |
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| 1.8538 | 3.0 | 1014 | 1.2525 | 0.7467 | |
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| 1.8538 | 4.0 | 1352 | 0.6251 | 0.8578 | |
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| 0.8758 | 5.0 | 1690 | 0.3761 | 0.8967 | |
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| 0.4181 | 6.0 | 2028 | 0.2852 | 0.9144 | |
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| 0.4181 | 7.0 | 2366 | 0.2492 | 0.9244 | |
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| 0.2458 | 8.0 | 2704 | 0.2169 | 0.9364 | |
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| 0.1721 | 9.0 | 3042 | 0.2121 | 0.9358 | |
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| 0.1721 | 10.0 | 3380 | 0.2052 | 0.9403 | |
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| 0.1089 | 11.0 | 3718 | 0.2075 | 0.9414 | |
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| 0.0783 | 12.0 | 4056 | 0.2164 | 0.9367 | |
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| 0.0783 | 13.0 | 4394 | 0.2274 | 0.9381 | |
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| 0.0573 | 14.0 | 4732 | 0.2196 | 0.9433 | |
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| 0.0465 | 15.0 | 5070 | 0.2415 | 0.9381 | |
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| 0.0465 | 16.0 | 5408 | 0.2370 | 0.9433 | |
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| 0.0375 | 17.0 | 5746 | 0.2521 | 0.94 | |
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| 0.0288 | 18.0 | 6084 | 0.2533 | 0.9411 | |
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| 0.0288 | 19.0 | 6422 | 0.2608 | 0.9381 | |
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| 0.0253 | 20.0 | 6760 | 0.2602 | 0.9397 | |
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| 0.0207 | 21.0 | 7098 | 0.2712 | 0.94 | |
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| 0.0207 | 22.0 | 7436 | 0.2584 | 0.9408 | |
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| 0.0187 | 23.0 | 7774 | 0.2703 | 0.9419 | |
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| 0.012 | 24.0 | 8112 | 0.2772 | 0.9422 | |
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| 0.012 | 25.0 | 8450 | 0.2712 | 0.9419 | |
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| 0.0174 | 26.0 | 8788 | 0.2774 | 0.9422 | |
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| 0.0137 | 27.0 | 9126 | 0.2857 | 0.9414 | |
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| 0.0137 | 28.0 | 9464 | 0.2796 | 0.9428 | |
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| 0.0111 | 29.0 | 9802 | 0.3008 | 0.9367 | |
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| 0.0106 | 30.0 | 10140 | 0.2938 | 0.9369 | |
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| 0.0106 | 31.0 | 10478 | 0.2863 | 0.9406 | |
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| 0.0079 | 32.0 | 10816 | 0.2903 | 0.9425 | |
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| 0.0078 | 33.0 | 11154 | 0.2961 | 0.9419 | |
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| 0.0078 | 34.0 | 11492 | 0.2882 | 0.9417 | |
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| 0.0056 | 35.0 | 11830 | 0.2974 | 0.9406 | |
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| 0.0041 | 36.0 | 12168 | 0.2997 | 0.9419 | |
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| 0.0039 | 37.0 | 12506 | 0.3123 | 0.9367 | |
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| 0.0039 | 38.0 | 12844 | 0.3009 | 0.9408 | |
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| 0.0036 | 39.0 | 13182 | 0.3009 | 0.9422 | |
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| 0.0055 | 40.0 | 13520 | 0.3093 | 0.9408 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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