metadata

license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12-192-22k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: swinv2-large-patch4-window12-192-22k-finetuned-ethzurich
    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: 0.8295454545454546

swinv2-large-patch4-window12-192-22k-finetuned-ethzurich

This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12-192-22k on the Urban Resource Cadastre dataset created by Deepika Raghu, Martin Juan José Bucher, and Catherine De Wolf (https://github.com/raghudeepika/urban-resource-cadastre-repository). It achieves the following results on the evaluation set:

Loss: 0.6083
Accuracy: 0.8295

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.96	6	1.2578	0.6364
1.6142	1.92	12	0.7696	0.75
1.6142	2.88	18	0.6083	0.8295

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3