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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: resnet-50-finetuned-resnet50_0831 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.976407675369613 |
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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-finetuned-resnet50_0831 |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0862 |
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- Accuracy: 0.9764 |
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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: 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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| 0.9066 | 1.0 | 223 | 0.8770 | 0.6659 | |
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| 0.5407 | 2.0 | 446 | 0.4251 | 0.7867 | |
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| 0.3614 | 3.0 | 669 | 0.2009 | 0.9390 | |
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| 0.3016 | 4.0 | 892 | 0.1362 | 0.9582 | |
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| 0.2358 | 5.0 | 1115 | 0.1139 | 0.9676 | |
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| 0.247 | 6.0 | 1338 | 0.1081 | 0.9698 | |
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| 0.2135 | 7.0 | 1561 | 0.1027 | 0.9720 | |
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| 0.2043 | 8.0 | 1784 | 0.1026 | 0.9695 | |
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| 0.2165 | 9.0 | 2007 | 0.0957 | 0.9733 | |
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| 0.1983 | 10.0 | 2230 | 0.0936 | 0.9736 | |
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| 0.2116 | 11.0 | 2453 | 0.0949 | 0.9736 | |
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| 0.2341 | 12.0 | 2676 | 0.0905 | 0.9755 | |
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| 0.2004 | 13.0 | 2899 | 0.0901 | 0.9739 | |
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| 0.1956 | 14.0 | 3122 | 0.0877 | 0.9755 | |
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| 0.1668 | 15.0 | 3345 | 0.0847 | 0.9764 | |
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| 0.1855 | 16.0 | 3568 | 0.0850 | 0.9755 | |
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| 0.18 | 17.0 | 3791 | 0.0897 | 0.9745 | |
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| 0.1772 | 18.0 | 4014 | 0.0852 | 0.9755 | |
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| 0.1881 | 19.0 | 4237 | 0.0845 | 0.9764 | |
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| 0.2145 | 20.0 | 4460 | 0.0862 | 0.9764 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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