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---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224
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: 0.7209302325581395
---
<!-- 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. -->
# vit-base-patch16-224
This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5932
- Accuracy: 0.7209
## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.96 | 6 | 0.7424 | 0.3488 |
| 0.7374 | 1.92 | 12 | 0.5932 | 0.7209 |
| 0.7374 | 2.88 | 18 | 0.5843 | 0.7209 |
| 0.5783 | 4.0 | 25 | 0.5996 | 0.7209 |
| 0.5358 | 4.96 | 31 | 0.6147 | 0.7209 |
| 0.5358 | 5.92 | 37 | 0.6159 | 0.7209 |
| 0.5745 | 6.88 | 43 | 0.6091 | 0.7209 |
| 0.5325 | 8.0 | 50 | 0.6067 | 0.7209 |
| 0.5325 | 8.96 | 56 | 0.6047 | 0.7209 |
| 0.524 | 9.6 | 60 | 0.6046 | 0.7209 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
|