metadata
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: spa_images_classifier_jd_v1_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: 0.9777571825764597
spa_images_classifier_jd_v1_convnext
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: 0.0652
- Accuracy: 0.9778
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 |
|---|---|---|---|---|
| 0.2494 | 1.0 | 227 | 0.1194 | 0.9555 |
| 0.2333 | 2.0 | 455 | 0.1008 | 0.9635 |
| 0.1977 | 3.0 | 683 | 0.0855 | 0.9703 |
| 0.1405 | 4.0 | 911 | 0.0792 | 0.9744 |
| 0.1575 | 5.0 | 1138 | 0.0734 | 0.9731 |
| 0.0948 | 6.0 | 1366 | 0.0666 | 0.9778 |
| 0.1049 | 7.0 | 1594 | 0.0662 | 0.9781 |
| 0.0928 | 8.0 | 1822 | 0.0693 | 0.9774 |
| 0.0903 | 9.0 | 2049 | 0.0704 | 0.9771 |
| 0.0759 | 9.97 | 2270 | 0.0652 | 0.9778 |
Framework versions
- Transformers 4.35.0
- Pytorch 1.12.1+cu113
- Datasets 2.17.1
- Tokenizers 0.14.1