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-fine_tune
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: 0.8781512605042017
swin-tiny-patch4-window7-224-fine_tune
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: 0.5958
- Accuracy: 0.8782
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.175 | 0.96 | 16 | 4.7967 | 0.1345 |
| 4.1158 | 1.97 | 33 | 2.9977 | 0.3824 |
| 2.0676 | 2.99 | 50 | 1.5415 | 0.6807 |
| 1.4395 | 4.0 | 67 | 0.9951 | 0.8151 |
| 0.9396 | 4.96 | 83 | 0.8235 | 0.8277 |
| 0.7456 | 5.97 | 100 | 0.7195 | 0.8361 |
| 0.666 | 6.99 | 117 | 0.6406 | 0.8613 |
| 0.5893 | 8.0 | 134 | 0.6045 | 0.8739 |
| 0.4704 | 8.96 | 150 | 0.6016 | 0.8655 |
| 0.4475 | 9.97 | 167 | 0.5958 | 0.8782 |
| 0.3937 | 10.99 | 184 | 0.5856 | 0.8782 |
| 0.3327 | 12.0 | 201 | 0.5761 | 0.8782 |
| 0.3277 | 12.96 | 217 | 0.5758 | 0.8782 |
| 0.2928 | 13.97 | 234 | 0.5754 | 0.8739 |
| 0.2545 | 14.99 | 251 | 0.5711 | 0.8739 |
| 0.2657 | 16.0 | 268 | 0.5851 | 0.8739 |
| 0.2457 | 16.96 | 284 | 0.5805 | 0.8655 |
| 0.2359 | 17.97 | 301 | 0.5762 | 0.8697 |
| 0.2849 | 18.99 | 318 | 0.5792 | 0.8739 |
| 0.223 | 19.1 | 320 | 0.5792 | 0.8739 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1