metadata
license: apache-2.0
base_model: microsoft/swin-large-patch4-window12-384-in22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-large-patch4-window12-384-in22k-finetuned-batch8
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: 0.9886363636363636
swin-large-patch4-window12-384-in22k-finetuned-batch8
This model is a fine-tuned version of microsoft/swin-large-patch4-window12-384-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0430
- Accuracy: 0.9886
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2123 | 0.9949 | 49 | 0.0916 | 0.9659 |
| 0.1613 | 1.9898 | 98 | 0.0430 | 0.9886 |
| 0.116 | 2.9848 | 147 | 0.0346 | 0.9886 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1