metadata
license: apache-2.0
base_model: Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp3
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-cp3
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: 0.5625
swin-tiny-patch4-window7-224-finetuned-cp3
This model is a fine-tuned version of Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp3 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.7607
- Accuracy: 0.5625
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 0.86 | 3 | 1.0238 | 0.2292 |
No log | 2.0 | 7 | 1.0684 | 0.2708 |
0.3856 | 2.86 | 10 | 0.7773 | 0.5208 |
0.3856 | 4.0 | 14 | 0.7619 | 0.5417 |
0.3856 | 4.29 | 15 | 0.7607 | 0.5625 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0