metadata
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-eurosat-leukemia-1000
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: 0.945
swin-tiny-patch4-window7-224-finetuned-eurosat-leukemia-1000
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: 0.2078
- Accuracy: 0.945
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 |
|---|---|---|---|---|
| 0.6899 | 0.9825 | 14 | 0.6198 | 0.6 |
| 0.5494 | 1.9649 | 28 | 0.4008 | 0.805 |
| 0.376 | 2.9474 | 42 | 0.4086 | 0.815 |
| 0.2852 | 4.0 | 57 | 0.4454 | 0.81 |
| 0.184 | 4.9825 | 71 | 0.8481 | 0.715 |
| 0.183 | 5.9649 | 85 | 0.1870 | 0.94 |
| 0.1465 | 6.9474 | 99 | 0.7121 | 0.8 |
| 0.1319 | 8.0 | 114 | 0.2078 | 0.945 |
| 0.1054 | 8.9825 | 128 | 0.3321 | 0.885 |
| 0.096 | 9.8246 | 140 | 0.3423 | 0.885 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1