metadata
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- image_folder
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: image_folder
type: image_folder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.598512173128945
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 image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6732
- Accuracy: 0.5985
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: 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 |
|---|---|---|---|---|
| 0.6726 | 1.0 | 329 | 0.6758 | 0.5985 |
| 0.6773 | 2.0 | 658 | 0.6738 | 0.5985 |
| 0.6701 | 3.0 | 987 | 0.6736 | 0.5985 |
| 0.6734 | 4.0 | 1317 | 0.6735 | 0.5985 |
| 0.671 | 5.0 | 1646 | 0.6738 | 0.5985 |
| 0.6725 | 6.0 | 1975 | 0.6740 | 0.5985 |
| 0.6702 | 7.0 | 2304 | 0.6737 | 0.5985 |
| 0.6708 | 8.0 | 2634 | 0.6733 | 0.5983 |
| 0.6732 | 9.0 | 2963 | 0.6735 | 0.5985 |
| 0.671 | 9.99 | 3290 | 0.6732 | 0.5985 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1