metadata

license: apache-2.0
base_model: NiharGupte/swin-tiny-patch4-window7-224-finetuned-student_six_classes
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: >-
      swin-tiny-patch4-window7-224-finetuned-student_six_classes-finetuned-student_six_classes
    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: 0.78

swin-tiny-patch4-window7-224-finetuned-student_six_classes-finetuned-student_six_classes

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

Loss: 0.5073
Accuracy: 0.78

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	0.9231	3	0.5972	0.78
No log	1.8462	6	0.9760	0.78
No log	2.7692	9	0.7597	0.78
0.5361	4.0	13	0.5870	0.78
0.5361	4.9231	16	0.5333	0.78
0.5361	5.8462	19	0.5040	0.78
0.4032	6.7692	22	0.4990	0.78
0.4032	8.0	26	0.5073	0.78
0.4032	8.9231	29	0.5070	0.78
0.3579	9.2308	30	0.5073	0.78

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1