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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-vosap
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: 0.5
---
<!-- 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-vosap
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: 0.5813
- Accuracy: 0.5
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 1 | 0.6077 | 0.5 |
| No log | 2.0 | 2 | 0.5957 | 0.5 |
| No log | 3.0 | 3 | 0.6554 | 0.5 |
| No log | 4.0 | 4 | 0.7486 | 0.25 |
| No log | 5.0 | 5 | 0.8207 | 0.25 |
| No log | 6.0 | 6 | 0.8213 | 0.25 |
| No log | 7.0 | 7 | 0.7957 | 0.5 |
| No log | 8.0 | 8 | 0.7098 | 0.5 |
| No log | 9.0 | 9 | 0.6372 | 0.5 |
| 0.2113 | 10.0 | 10 | 0.5358 | 0.5 |
| 0.2113 | 11.0 | 11 | 0.4894 | 0.75 |
| 0.2113 | 12.0 | 12 | 0.4507 | 0.75 |
| 0.2113 | 13.0 | 13 | 0.4311 | 0.75 |
| 0.2113 | 14.0 | 14 | 0.4339 | 0.75 |
| 0.2113 | 15.0 | 15 | 0.4600 | 0.75 |
| 0.2113 | 16.0 | 16 | 0.4982 | 0.5 |
| 0.2113 | 17.0 | 17 | 0.5299 | 0.5 |
| 0.2113 | 18.0 | 18 | 0.5602 | 0.5 |
| 0.2113 | 19.0 | 19 | 0.5777 | 0.5 |
| 0.0955 | 20.0 | 20 | 0.5813 | 0.5 |
### Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
|