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update model card README.md
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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-drfx-surgery-classifier
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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: 0.875
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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-drfx-surgery-classifier
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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: 0.6525
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- Accuracy: 0.875
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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-06
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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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: 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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| No log | 1.0 | 4 | 0.6591 | 0.8125 |
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| No log | 2.0 | 8 | 0.6399 | 0.875 |
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| 0.6638 | 3.0 | 12 | 0.6671 | 0.875 |
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| 0.6638 | 4.0 | 16 | 0.6645 | 0.8125 |
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| 0.6562 | 5.0 | 20 | 0.6495 | 0.875 |
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| 0.6562 | 6.0 | 24 | 0.6673 | 0.875 |
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| 0.6562 | 7.0 | 28 | 0.6539 | 0.875 |
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| 0.6527 | 8.0 | 32 | 0.6519 | 0.875 |
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| 0.6527 | 9.0 | 36 | 0.6603 | 0.875 |
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| 0.6596 | 10.0 | 40 | 0.6525 | 0.875 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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