metadata
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: custom-cloud-model
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: 0.9506173133850098
custom-cloud-model
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2242
- Accuracy: 0.9506
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.153 | 1.0 | 80 | 0.9964 | 0.7510 |
| 0.8046 | 2.0 | 160 | 0.4400 | 0.8477 |
| 0.7706 | 3.0 | 240 | 0.5513 | 0.8107 |
| 0.6695 | 4.0 | 320 | 0.2639 | 0.9136 |
| 0.4697 | 5.0 | 400 | 0.2199 | 0.9300 |
| 0.4564 | 6.0 | 480 | 0.1808 | 0.9321 |
| 0.4094 | 7.0 | 560 | 0.2471 | 0.9239 |
| 0.2445 | 8.0 | 640 | 0.1998 | 0.9424 |
| 0.3153 | 9.0 | 720 | 0.2600 | 0.9136 |
| 0.1994 | 10.0 | 800 | 0.3160 | 0.9259 |
| 0.2205 | 11.0 | 880 | 0.2486 | 0.9239 |
| 0.2312 | 12.0 | 960 | 0.2131 | 0.9486 |
| 0.2382 | 13.0 | 1040 | 0.2487 | 0.9239 |
| 0.1158 | 14.0 | 1120 | 0.2153 | 0.9506 |
| 0.1 | 15.0 | 1200 | 0.2271 | 0.9486 |
| 0.0916 | 16.0 | 1280 | 0.2626 | 0.9259 |
| 0.1021 | 17.0 | 1360 | 0.2130 | 0.9403 |
| 0.0991 | 18.0 | 1440 | 0.2240 | 0.9444 |
| 0.0526 | 19.0 | 1520 | 0.2353 | 0.9506 |
| 0.0461 | 20.0 | 1600 | 0.2137 | 0.9506 |
| 0.0832 | 21.0 | 1680 | 0.2215 | 0.9444 |
| 0.0708 | 22.0 | 1760 | 0.2114 | 0.9506 |
| 0.1027 | 23.0 | 1840 | 0.2104 | 0.9527 |
| 0.0292 | 24.0 | 1920 | 0.2346 | 0.9547 |
| 0.033 | 25.0 | 2000 | 0.2242 | 0.9506 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1