README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: >-
      swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e-finetuned-og-dataset-10e
    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: 0.9782978378816098

swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e-finetuned-og-dataset-10e

This model is a fine-tuned version of Gokulapriyan/swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.0556
• Accuracy: 0.9783

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2237	1.0	546	0.0729	0.9735
0.1672	2.0	1092	0.0556	0.9783

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2