|
--- |
|
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: 0.76 |
|
--- |
|
|
|
<!-- 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-student_two_classes |
|
|
|
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: 0.7437 |
|
- Accuracy: 0.76 |
|
|
|
## 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 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.3845 | 1.0 | 13 | 0.6475 | 0.7 | |
|
| 0.3466 | 2.0 | 26 | 0.6201 | 0.74 | |
|
| 0.3832 | 3.0 | 39 | 0.8068 | 0.82 | |
|
| 0.5344 | 4.0 | 52 | 0.6340 | 0.81 | |
|
| 0.4912 | 5.0 | 65 | 0.6880 | 0.8 | |
|
| 0.5093 | 6.0 | 78 | 0.6999 | 0.73 | |
|
| 0.4109 | 7.0 | 91 | 0.7295 | 0.83 | |
|
| 0.4383 | 8.0 | 104 | 0.7048 | 0.84 | |
|
| 0.4534 | 9.0 | 117 | 0.6094 | 0.82 | |
|
| 0.4684 | 10.0 | 130 | 0.5789 | 0.74 | |
|
| 0.3442 | 11.0 | 143 | 0.7297 | 0.82 | |
|
| 0.3236 | 12.0 | 156 | 0.7688 | 0.79 | |
|
| 0.4645 | 13.0 | 169 | 0.6687 | 0.76 | |
|
| 0.3532 | 14.0 | 182 | 0.7880 | 0.84 | |
|
| 0.3394 | 15.0 | 195 | 0.7216 | 0.79 | |
|
| 0.3311 | 16.0 | 208 | 0.7209 | 0.79 | |
|
| 0.3367 | 17.0 | 221 | 0.6827 | 0.71 | |
|
| 0.3673 | 18.0 | 234 | 0.7472 | 0.76 | |
|
| 0.3024 | 19.0 | 247 | 0.7761 | 0.79 | |
|
| 0.3624 | 20.0 | 260 | 0.7437 | 0.76 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.1 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
