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README.md
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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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datasets:
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- imagefolder
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.44188861985472155
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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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# my__model
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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: 1.3439
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- Accuracy: 0.4419
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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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- Transformers 4.42.4
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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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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- code
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datasets:
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- imagefolder
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.44188861985472155
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pipeline_tag: image-classification
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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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# my__model
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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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with specialised focus on kneeosteoarthritis data.
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It achieves the following results on the evaluation set:
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- Loss: 1.3439
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- Accuracy: 0.4419
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## Model description
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model built to refine the classification with specialised focus on kneeosteoarthritis data.
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for medical data related to similar domains can use the same to finetune further.
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## Intended uses & limitations
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More information needed
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### Training hyperparameters
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- Transformers 4.42.4
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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