transformers tensorboard safetensors swin image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/swin-tiny-patch4-window7-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
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
---

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# 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
