README.md

metadata

tags:
  - image-classification
  - timm
  - generated_from_trainer
datasets:
  - beans
metrics:
  - accuracy
model_index:
  - name: timm-resnet18-beans-test-2
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: beans
          type: beans
          args: default
        metric:
          name: Accuracy
          type: accuracy
          value: 0.5789473684210527
base_model: resnet18

timm-resnet18-beans-test-2

This model is a fine-tuned version of resnet18 on the beans dataset. It achieves the following results on the evaluation set:

• Loss: 1.3225
• Accuracy: 0.5789

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: 0.001
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2601	0.02	5	2.8349	0.5113
1.8184	0.04	10	1.3225	0.5789

Framework versions

• Transformers 4.9.1
• Pytorch 1.9.0
• Datasets 1.11.1.dev0
• Tokenizers 0.10.3