metadata
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_classifier_v1
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: 0.9374278867489128
swin-tiny-patch4-window7-224-hotel_classifier_v1
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1932
- Accuracy: 0.9374
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 |
|---|---|---|---|---|
| 0.3281 | 1.0 | 792 | 0.2726 | 0.9074 |
| 0.3858 | 2.0 | 1584 | 0.2388 | 0.9191 |
| 0.3153 | 3.0 | 2376 | 0.2123 | 0.9270 |
| 0.3438 | 4.0 | 3169 | 0.2063 | 0.9289 |
| 0.3219 | 5.0 | 3961 | 0.2061 | 0.9283 |
| 0.2293 | 6.0 | 4753 | 0.1965 | 0.9333 |
| 0.264 | 7.0 | 5545 | 0.1966 | 0.9360 |
| 0.2112 | 8.0 | 6338 | 0.1964 | 0.9340 |
| 0.2716 | 9.0 | 7130 | 0.1969 | 0.9350 |
| 0.1938 | 10.0 | 7920 | 0.1932 | 0.9374 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2