metadata

license: apache-2.0
base_model: microsoft/swin-large-patch4-window12-384-in22k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: swin-large-patch4-window12-384-in22k-finetuned-batch8
    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: 0.9886363636363636

swin-large-patch4-window12-384-in22k-finetuned-batch8

This model is a fine-tuned version of microsoft/swin-large-patch4-window12-384-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0430
Accuracy: 0.9886

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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
0.2123	0.9949	49	0.0916	0.9659
0.1613	1.9898	98	0.0430	0.9886
0.116	2.9848	147	0.0346	0.9886

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1