---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hotel_images_classifier_jd_v4_convnext
  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: 0.936588653351305
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hotel_images_classifier_jd_v4_convnext

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: 0.1917
- Accuracy: 0.9366

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3471        | 1.0   | 1147 | 0.2357          | 0.9215   |
| 0.2737        | 2.0   | 2295 | 0.2133          | 0.9280   |
| 0.2743        | 3.0   | 3443 | 0.1934          | 0.9355   |
| 0.276         | 4.0   | 4591 | 0.1982          | 0.9329   |
| 0.2324        | 5.0   | 5735 | 0.1917          | 0.9366   |


### Framework versions

- Transformers 4.35.0
- Pytorch 1.12.1+cu113
- Datasets 2.17.1
- Tokenizers 0.14.1