README.md

metadata

license: apache-2.0
base_model: microsoft/resnet-152
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: resnet-152-finetuned-cassava-leaf-disease
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.3560747663551402

resnet-152-finetuned-cassava-leaf-disease

This model is a fine-tuned version of microsoft/resnet-152 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 4.1197
• Accuracy: 0.3561

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: 200
• eval_batch_size: 200
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 800
• 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
6.4984	0.99	24	5.4849	0.0771
5.2526	1.98	48	4.2884	0.3290
4.118	2.97	72	4.1197	0.3561

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.1
• Datasets 2.18.0
• Tokenizers 0.15.1