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---
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-hotel_images_classifier_v5_10epocs
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: 0.9558704453441296
---
<!-- 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-hotel_images_classifier_v5_10epocs
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: 0.1293
- Accuracy: 0.9559
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3795 | 1.0 | 694 | 0.1922 | 0.9326 |
| 0.261 | 2.0 | 1389 | 0.1850 | 0.9335 |
| 0.2187 | 3.0 | 2084 | 0.1516 | 0.9448 |
| 0.1491 | 4.0 | 2779 | 0.1360 | 0.9518 |
| 0.2038 | 5.0 | 3473 | 0.1312 | 0.9514 |
| 0.1793 | 6.0 | 4168 | 0.1290 | 0.9522 |
| 0.19 | 7.0 | 4863 | 0.1332 | 0.9533 |
| 0.1424 | 8.0 | 5558 | 0.1297 | 0.9549 |
| 0.1555 | 9.0 | 6252 | 0.1303 | 0.9552 |
| 0.1238 | 9.99 | 6940 | 0.1293 | 0.9559 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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