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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-shortSleeveCleanedData |
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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: 0.9781420765027322 |
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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-shortSleeveCleanedData |
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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: 0.1103 |
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- Accuracy: 0.9781 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 7 |
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- total_train_batch_size: 56 |
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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: 0.01 |
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- num_epochs: 10 |
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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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| 0.973 | 1.0 | 147 | 0.9371 | 0.7268 | |
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| 0.6565 | 2.0 | 294 | 0.5520 | 0.8710 | |
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| 0.4609 | 3.0 | 441 | 0.2983 | 0.9279 | |
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| 0.3937 | 4.0 | 588 | 0.2051 | 0.9486 | |
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| 0.3723 | 5.0 | 735 | 0.1521 | 0.9727 | |
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| 0.3926 | 6.0 | 882 | 0.1490 | 0.9672 | |
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| 0.3326 | 7.0 | 1029 | 0.1367 | 0.9650 | |
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| 0.3166 | 8.0 | 1176 | 0.1109 | 0.9738 | |
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| 0.3492 | 9.0 | 1323 | 0.1108 | 0.9760 | |
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| 0.3228 | 10.0 | 1470 | 0.1103 | 0.9781 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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