|
--- |
|
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-sealv1 |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: validation |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9119804400977995 |
|
--- |
|
|
|
<!-- 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-sealv1 |
|
|
|
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: 0.2553 |
|
- Accuracy: 0.9120 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.1068 | 0.95 | 14 | 0.6518 | 0.7066 | |
|
| 0.4912 | 1.97 | 29 | 0.4668 | 0.8435 | |
|
| 0.2749 | 2.98 | 44 | 0.4127 | 0.8704 | |
|
| 0.3189 | 4.0 | 59 | 0.3626 | 0.8875 | |
|
| 0.2226 | 4.95 | 73 | 0.2638 | 0.9046 | |
|
| 0.2394 | 5.97 | 88 | 0.3584 | 0.8802 | |
|
| 0.2241 | 6.98 | 103 | 0.2821 | 0.9046 | |
|
| 0.1815 | 8.0 | 118 | 0.2138 | 0.9218 | |
|
| 0.1862 | 8.95 | 132 | 0.2738 | 0.9046 | |
|
| 0.1942 | 9.49 | 140 | 0.2553 | 0.9120 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 1.10.2+cu113 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
