metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-bottom_cleaned_data-hpt
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: 0.9694041867954911
swin-tiny-patch4-window7-224-bottom_cleaned_data-hpt
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: 0.0701
- Accuracy: 0.9694
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4307 | 0.99 | 99 | 0.2332 | 0.9227 |
| 0.3425 | 2.0 | 199 | 0.1904 | 0.9404 |
| 0.29 | 3.0 | 299 | 0.1316 | 0.9388 |
| 0.2597 | 3.99 | 398 | 0.1158 | 0.9533 |
| 0.2638 | 4.99 | 498 | 0.0987 | 0.9614 |
| 0.209 | 6.0 | 598 | 0.0802 | 0.9710 |
| 0.1776 | 7.0 | 698 | 0.0838 | 0.9597 |
| 0.1776 | 7.99 | 797 | 0.0787 | 0.9694 |
| 0.1502 | 9.0 | 897 | 0.0797 | 0.9726 |
| 0.1402 | 9.93 | 990 | 0.0701 | 0.9694 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3