|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: swin-tiny-patch4-window7-224-finetuned-woody |
|
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: 0.7927272727272727 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# swin-tiny-patch4-window7-224-finetuned-woody |
|
|
|
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4349 |
|
- Accuracy: 0.7927 |
|
|
|
## 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: 30 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.632 | 1.0 | 58 | 0.5883 | 0.6836 | |
|
| 0.6067 | 2.0 | 116 | 0.6017 | 0.6848 | |
|
| 0.5865 | 3.0 | 174 | 0.5695 | 0.7042 | |
|
| 0.553 | 4.0 | 232 | 0.5185 | 0.7515 | |
|
| 0.5468 | 5.0 | 290 | 0.5108 | 0.7430 | |
|
| 0.5473 | 6.0 | 348 | 0.4882 | 0.7648 | |
|
| 0.5381 | 7.0 | 406 | 0.4800 | 0.7588 | |
|
| 0.5468 | 8.0 | 464 | 0.5056 | 0.7358 | |
|
| 0.5191 | 9.0 | 522 | 0.4784 | 0.7673 | |
|
| 0.5318 | 10.0 | 580 | 0.4762 | 0.7636 | |
|
| 0.5079 | 11.0 | 638 | 0.4859 | 0.7673 | |
|
| 0.5216 | 12.0 | 696 | 0.4691 | 0.7697 | |
|
| 0.515 | 13.0 | 754 | 0.4857 | 0.7624 | |
|
| 0.5186 | 14.0 | 812 | 0.4685 | 0.7733 | |
|
| 0.4748 | 15.0 | 870 | 0.4536 | 0.7818 | |
|
| 0.4853 | 16.0 | 928 | 0.4617 | 0.7770 | |
|
| 0.4868 | 17.0 | 986 | 0.4622 | 0.7782 | |
|
| 0.4572 | 18.0 | 1044 | 0.4583 | 0.7770 | |
|
| 0.4679 | 19.0 | 1102 | 0.4590 | 0.7733 | |
|
| 0.4508 | 20.0 | 1160 | 0.4576 | 0.7903 | |
|
| 0.4663 | 21.0 | 1218 | 0.4542 | 0.7891 | |
|
| 0.4533 | 22.0 | 1276 | 0.4428 | 0.7903 | |
|
| 0.4892 | 23.0 | 1334 | 0.4372 | 0.7867 | |
|
| 0.4704 | 24.0 | 1392 | 0.4414 | 0.7903 | |
|
| 0.4304 | 25.0 | 1450 | 0.4430 | 0.7988 | |
|
| 0.4411 | 26.0 | 1508 | 0.4348 | 0.7818 | |
|
| 0.4604 | 27.0 | 1566 | 0.4387 | 0.7927 | |
|
| 0.441 | 28.0 | 1624 | 0.4378 | 0.7964 | |
|
| 0.442 | 29.0 | 1682 | 0.4351 | 0.7915 | |
|
| 0.4585 | 30.0 | 1740 | 0.4349 | 0.7927 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.23.1 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.6.0 |
|
- Tokenizers 0.13.1 |
|
|
