README.md

metadata

license: other
base_model: apple/mobilevit-xx-small
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: vit-base-plankton
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: plankton_fairscope
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8050847457627118

vit-base-plankton

This model is a fine-tuned version of apple/mobilevit-xx-small on the plankton_fairscope dataset. It achieves the following results on the evaluation set:

• Loss: 0.7642
• Accuracy: 0.8051

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: 0.0002
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.5476	0.52	100	1.2745	0.7419
1.0997	1.04	200	0.8653	0.7842
0.9498	1.56	300	0.7642	0.8051

Framework versions

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