|
---
|
|
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-ve-U13-b-12
|
|
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: 0.5434782608695652
|
|
---
|
|
|
|
<!-- 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-ve-U13-b-12
|
|
|
|
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: 0.9160
|
|
- Accuracy: 0.5435
|
|
|
|
## 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: 12
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
|
| No log | 1.0 | 8 | 1.3788 | 0.4348 |
|
|
| 1.3828 | 2.0 | 16 | 1.3084 | 0.5 |
|
|
| 1.2902 | 3.0 | 24 | 1.1908 | 0.4783 |
|
|
| 1.1227 | 4.0 | 32 | 1.1055 | 0.4130 |
|
|
| 0.9806 | 5.0 | 40 | 1.0173 | 0.5217 |
|
|
| 0.9806 | 6.0 | 48 | 0.9396 | 0.5217 |
|
|
| 0.8629 | 7.0 | 56 | 0.9529 | 0.5 |
|
|
| 0.7707 | 8.0 | 64 | 0.9449 | 0.5217 |
|
|
| 0.7411 | 9.0 | 72 | 0.9160 | 0.5435 |
|
|
| 0.671 | 10.0 | 80 | 0.9073 | 0.5435 |
|
|
| 0.671 | 11.0 | 88 | 0.9192 | 0.5435 |
|
|
| 0.6501 | 12.0 | 96 | 0.9456 | 0.5 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.36.2
|
|
- Pytorch 2.1.2+cu118
|
|
- Datasets 2.16.1
|
|
- Tokenizers 0.15.0
|
|
|