README.md

metadata

license: apache-2.0
base_model: microsoft/resnet-50
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
widget:
  - src: >-
      https://huggingface.co/Alex14005/model-Dementia-classification-Alejandro-Arroyo/raw/main/Mild-demented.jpg
    example_title: Mild Demented
  - src: >-
      https://huggingface.co/Alex14005/model-Dementia-classification-Alejandro-Arroyo/raw/main/No-demented.jpg
    example_title: Healthy
model-index:
  - name: model-Dementia-classification-Alejandro-Arroyo
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: RiniPL/Dementia_Dataset
          type: imagefolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9230769230769231

model-Dementia-classification-Alejandro-Arroyo

This model is a fine-tuned version of microsoft/resnet-50 on the RiniPL/Dementia_Dataset dataset. It achieves the following results on the evaluation set:

• Loss: 0.1858
• Accuracy: 0.9231

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3