shivarama23's picture
update model card README.md
2d14522
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
model-index:
  - name: swin-tiny-patch4-window7-224-finetuned-image_quality
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9090909090909091

swin-tiny-patch4-window7-224-finetuned-image_quality

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the image_folder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5242
  • Accuracy: 0.9091

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: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 1 0.6762 0.6364
No log 2.0 2 0.6309 0.7273
No log 3.0 3 0.6095 0.6364
No log 4.0 4 0.5775 0.6364
No log 5.0 5 0.5443 0.8182
No log 6.0 6 0.5242 0.9091
No log 7.0 7 0.5149 0.8182
No log 8.0 8 0.5094 0.8182
No log 9.0 9 0.5038 0.8182
0.4095 10.0 10 0.4992 0.8182

Framework versions

  • Transformers 4.19.4
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1