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-MM_Classification
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: 0.8693982074263764
swin-tiny-patch4-window7-224-MM_Classification
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: 0.3468
- Accuracy: 0.8694
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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0476 | 1.0 | 19 | 0.7707 | 0.6530 |
| 0.6226 | 2.0 | 38 | 0.4743 | 0.8105 |
| 0.4477 | 3.0 | 57 | 0.4133 | 0.8323 |
| 0.3963 | 4.0 | 76 | 0.3813 | 0.8476 |
| 0.3694 | 5.0 | 95 | 0.3753 | 0.8540 |
| 0.3451 | 6.0 | 114 | 0.3587 | 0.8489 |
| 0.3382 | 7.0 | 133 | 0.3531 | 0.8451 |
| 0.3253 | 8.0 | 152 | 0.3498 | 0.8579 |
| 0.3121 | 9.0 | 171 | 0.3437 | 0.8579 |
| 0.2855 | 10.0 | 190 | 0.3447 | 0.8656 |
| 0.2961 | 11.0 | 209 | 0.3350 | 0.8617 |
| 0.273 | 12.0 | 228 | 0.3484 | 0.8566 |
| 0.2745 | 13.0 | 247 | 0.3433 | 0.8604 |
| 0.2613 | 14.0 | 266 | 0.3498 | 0.8643 |
| 0.2527 | 15.0 | 285 | 0.3365 | 0.8579 |
| 0.2619 | 16.0 | 304 | 0.3450 | 0.8617 |
| 0.2436 | 17.0 | 323 | 0.3454 | 0.8681 |
| 0.2518 | 18.0 | 342 | 0.3437 | 0.8681 |
| 0.243 | 19.0 | 361 | 0.3468 | 0.8694 |
| 0.2415 | 20.0 | 380 | 0.3455 | 0.8694 |
Framework versions
- Transformers 4.43.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1