|
--- |
|
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-MM_Classification |
|
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: 0.8693982074263764 |
|
--- |
|
|
|
<!-- 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-MM_Classification |
|
|
|
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: 0.3468 |
|
- Accuracy: 0.8694 |
|
|
|
## 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: 128 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 512 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.0476 | 1.0 | 19 | 0.7707 | 0.6530 | |
|
| 0.6226 | 2.0 | 38 | 0.4743 | 0.8105 | |
|
| 0.4477 | 3.0 | 57 | 0.4133 | 0.8323 | |
|
| 0.3963 | 4.0 | 76 | 0.3813 | 0.8476 | |
|
| 0.3694 | 5.0 | 95 | 0.3753 | 0.8540 | |
|
| 0.3451 | 6.0 | 114 | 0.3587 | 0.8489 | |
|
| 0.3382 | 7.0 | 133 | 0.3531 | 0.8451 | |
|
| 0.3253 | 8.0 | 152 | 0.3498 | 0.8579 | |
|
| 0.3121 | 9.0 | 171 | 0.3437 | 0.8579 | |
|
| 0.2855 | 10.0 | 190 | 0.3447 | 0.8656 | |
|
| 0.2961 | 11.0 | 209 | 0.3350 | 0.8617 | |
|
| 0.273 | 12.0 | 228 | 0.3484 | 0.8566 | |
|
| 0.2745 | 13.0 | 247 | 0.3433 | 0.8604 | |
|
| 0.2613 | 14.0 | 266 | 0.3498 | 0.8643 | |
|
| 0.2527 | 15.0 | 285 | 0.3365 | 0.8579 | |
|
| 0.2619 | 16.0 | 304 | 0.3450 | 0.8617 | |
|
| 0.2436 | 17.0 | 323 | 0.3454 | 0.8681 | |
|
| 0.2518 | 18.0 | 342 | 0.3437 | 0.8681 | |
|
| 0.243 | 19.0 | 361 | 0.3468 | 0.8694 | |
|
| 0.2415 | 20.0 | 380 | 0.3455 | 0.8694 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.43.3 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
