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---
license: apache-2.0
base_model: microsoft/swin-large-patch4-window12-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya2_SGD_1e3_20Epoch_Swin-large-224_fold1
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.47160493827160493
---
<!-- 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. -->
# Boya2_SGD_1e3_20Epoch_Swin-large-224_fold1
This model is a fine-tuned version of [microsoft/swin-large-patch4-window12-384](https://huggingface.co/microsoft/swin-large-patch4-window12-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6332
- Accuracy: 0.4716
## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4897 | 1.0 | 914 | 2.4409 | 0.2804 |
| 2.1506 | 2.0 | 1828 | 2.2233 | 0.2968 |
| 2.0176 | 3.0 | 2742 | 2.1001 | 0.3311 |
| 1.9799 | 4.0 | 3656 | 2.0112 | 0.3564 |
| 1.9403 | 5.0 | 4570 | 1.9459 | 0.3786 |
| 1.9907 | 6.0 | 5484 | 1.8909 | 0.4003 |
| 1.7985 | 7.0 | 6398 | 1.8449 | 0.4159 |
| 1.8712 | 8.0 | 7312 | 1.8057 | 0.4239 |
| 1.7195 | 9.0 | 8226 | 1.7733 | 0.4348 |
| 1.8526 | 10.0 | 9140 | 1.7458 | 0.4436 |
| 1.67 | 11.0 | 10054 | 1.7203 | 0.4488 |
| 1.6061 | 12.0 | 10968 | 1.7023 | 0.4549 |
| 1.6256 | 13.0 | 11882 | 1.6832 | 0.4582 |
| 1.8212 | 14.0 | 12796 | 1.6685 | 0.4634 |
| 1.7157 | 15.0 | 13710 | 1.6584 | 0.4639 |
| 1.6148 | 16.0 | 14624 | 1.6491 | 0.4661 |
| 1.7158 | 17.0 | 15538 | 1.6424 | 0.4675 |
| 1.7391 | 18.0 | 16452 | 1.6370 | 0.4689 |
| 1.8077 | 19.0 | 17366 | 1.6337 | 0.4716 |
| 1.7769 | 20.0 | 18280 | 1.6332 | 0.4716 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.21.0
- Tokenizers 0.13.2
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