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update model card README.md

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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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+
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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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+
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+ # resnet-50-shortSleeveCleanedData
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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