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-finetuned-soccer-binary
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: 0.9714285714285714
swin-tiny-patch4-window7-224-finetuned-soccer-binary
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: 0.1138
- Accuracy: 0.9714
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 |
|---|---|---|---|---|
| 0.1286 | 0.96 | 12 | 0.1138 | 0.9714 |
| 0.1267 | 2.0 | 25 | 0.1283 | 0.9657 |
| 0.121 | 2.96 | 37 | 0.1124 | 0.9657 |
| 0.1142 | 4.0 | 50 | 0.1151 | 0.9657 |
| 0.1069 | 4.96 | 62 | 0.1063 | 0.96 |
| 0.1038 | 6.0 | 75 | 0.1210 | 0.96 |
| 0.0935 | 6.96 | 87 | 0.1150 | 0.96 |
| 0.1042 | 8.0 | 100 | 0.1038 | 0.9657 |
| 0.0945 | 8.96 | 112 | 0.1071 | 0.96 |
| 0.0891 | 9.6 | 120 | 0.1077 | 0.96 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1