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-Mid-NonMidMarket-Classification
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: 0.8425624321389794
swin-tiny-patch4-window7-224-Mid-NonMidMarket-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: 0.4046
- Accuracy: 0.8426
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 |
|---|---|---|---|---|
| 0.5809 | 0.9884 | 64 | 0.5024 | 0.7937 |
| 0.5326 | 1.9923 | 129 | 0.4402 | 0.8132 |
| 0.4626 | 2.9961 | 194 | 0.4244 | 0.8284 |
| 0.4778 | 4.0 | 259 | 0.4234 | 0.8274 |
| 0.4109 | 4.9884 | 323 | 0.4197 | 0.8306 |
| 0.3764 | 5.9923 | 388 | 0.4095 | 0.8295 |
| 0.3725 | 6.9961 | 453 | 0.4046 | 0.8426 |
| 0.3583 | 8.0 | 518 | 0.4109 | 0.8371 |
| 0.3451 | 8.9884 | 582 | 0.4171 | 0.8350 |
| 0.3351 | 9.8842 | 640 | 0.4153 | 0.8404 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1