metadata
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224-in22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-in22k-MM_Classification_base_web_images
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8837955535182214
swin-base-patch4-window7-224-in22k-MM_Classification_base_web_images
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3017
- Accuracy: 0.8838
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.517 | 0.9927 | 68 | 0.4430 | 0.8157 |
| 0.4211 | 2.0 | 137 | 0.3800 | 0.8457 |
| 0.3532 | 2.9927 | 205 | 0.3563 | 0.8616 |
| 0.3365 | 4.0 | 274 | 0.3333 | 0.8700 |
| 0.2976 | 4.9927 | 342 | 0.3017 | 0.8838 |
| 0.2611 | 6.0 | 411 | 0.3119 | 0.8810 |
| 0.255 | 6.9489 | 476 | 0.3085 | 0.8820 |
Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1