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-student_two_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_two_classes
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: 0.4645
- 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 | 0.5091 | 0.79 |
| No log | 1.8462 | 6 | 0.6119 | 0.78 |
| No log | 2.7692 | 9 | 0.5369 | 0.78 |
| 0.5446 | 4.0 | 13 | 0.4780 | 0.78 |
| 0.5446 | 4.9231 | 16 | 0.4721 | 0.78 |
| 0.5446 | 5.8462 | 19 | 0.4750 | 0.78 |
| 0.4041 | 6.7692 | 22 | 0.4746 | 0.78 |
| 0.4041 | 8.0 | 26 | 0.4700 | 0.78 |
| 0.4041 | 8.9231 | 29 | 0.4649 | 0.78 |
| 0.3755 | 9.2308 | 30 | 0.4645 | 0.78 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1