README.md

metadata

tags:
  - image-classification
  - vision
  - generated_from_trainer
datasets:
  - AI-Lab-Makerere/beans
metrics:
  - accuracy
model-index:
  - name: resnet-50-base-beans-demo
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: beans
          type: beans
          args: default
        metrics:
          - type: accuracy
            value: 0.9022556390977443
            name: Accuracy

resnet-50-base-beans-demo

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

• Loss: 0.2188
• Accuracy: 0.9023

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: 0.002
• train_batch_size: 8
• eval_batch_size: 8
• seed: 1337
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5679	1.0	130	0.2188	0.9023

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu102
• Datasets 2.2.1
• Tokenizers 0.12.1