README.md

metadata

license: apache-2.0
base_model: microsoft/resnet-50
tags:
  - generated_from_trainer
datasets:
  - chest-xray-classification
metrics:
  - accuracy
model-index:
  - name: Cheese_xray
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: chest-xray-classification
          type: chest-xray-classification
          config: full
          split: test
          args: full
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7061855670103093

Cheese_xray

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

• Loss: 0.4278
• Accuracy: 0.7062

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5547	0.99	63	0.5554	0.7062
0.4303	1.99	127	0.4387	0.7079
0.4377	2.96	189	0.4278	0.7062

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0