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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e-finetuned-og-dataset-10e
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: 0.9782978378816098
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e-finetuned-og-dataset-10e
This model is a fine-tuned version of [Gokulapriyan/swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e](https://huggingface.co/Gokulapriyan/swinv2-tiny-patch4-window8-256-finetuned-og-dataset-10e) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0556
- Accuracy: 0.9783
## 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2237 | 1.0 | 546 | 0.0729 | 0.9735 |
| 0.1672 | 2.0 | 1092 | 0.0556 | 0.9783 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2