metadata
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-skin-cancer
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: 0.8772455089820359
swin-tiny-patch4-window7-224-finetuned-skin-cancer
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3211
- Accuracy: 0.8772
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 |
|---|---|---|---|---|
| 0.8717 | 0.9929 | 35 | 0.8160 | 0.6916 |
| 0.6289 | 1.9858 | 70 | 0.5764 | 0.8034 |
| 0.4878 | 2.9787 | 105 | 0.4994 | 0.8174 |
| 0.4392 | 4.0 | 141 | 0.4301 | 0.8493 |
| 0.3867 | 4.9929 | 176 | 0.4034 | 0.8573 |
| 0.3653 | 5.9858 | 211 | 0.3476 | 0.8693 |
| 0.3359 | 6.9787 | 246 | 0.3681 | 0.8643 |
| 0.2865 | 8.0 | 282 | 0.3578 | 0.8653 |
| 0.3041 | 8.9929 | 317 | 0.3245 | 0.8792 |
| 0.2869 | 9.9291 | 350 | 0.3211 | 0.8772 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0