metadata
library_name: transformers
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-mobile-eye-tracking-dataset-v2
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: 0.8257839721254355
swin-tiny-patch4-window7-224-finetuned-mobile-eye-tracking-dataset-v2
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: 0.4614
- Accuracy: 0.8258
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 |
|---|---|---|---|---|
| 1.8826 | 1.0 | 64 | 1.5673 | 0.4669 |
| 1.1123 | 2.0 | 128 | 0.9031 | 0.7154 |
| 0.8883 | 3.0 | 192 | 0.7255 | 0.7573 |
| 0.7778 | 4.0 | 256 | 0.6219 | 0.7793 |
| 0.708 | 5.0 | 320 | 0.5521 | 0.8002 |
| 0.6308 | 6.0 | 384 | 0.5193 | 0.8130 |
| 0.6142 | 7.0 | 448 | 0.4854 | 0.8235 |
| 0.5817 | 8.0 | 512 | 0.4726 | 0.8200 |
| 0.5952 | 9.0 | 576 | 0.4648 | 0.8211 |
| 0.5915 | 10.0 | 640 | 0.4614 | 0.8258 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0