metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-in21k-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: 0.9885350318471338
vit-base-patch16-224-in21k-mobile-eye-tracking-dataset-v2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0657
- Accuracy: 0.9885
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: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- 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 |
|---|---|---|---|---|
| 0.024 | 0.99 | 73 | 0.0769 | 0.9809 |
| 0.0236 | 1.99 | 147 | 0.1111 | 0.9745 |
| 0.0172 | 3.0 | 221 | 0.0542 | 0.9898 |
| 0.0114 | 4.0 | 295 | 0.0630 | 0.9885 |
| 0.0051 | 4.99 | 368 | 0.0674 | 0.9860 |
| 0.0044 | 5.99 | 442 | 0.0640 | 0.9885 |
| 0.0037 | 7.0 | 516 | 0.0646 | 0.9885 |
| 0.0034 | 8.0 | 590 | 0.0652 | 0.9885 |
| 0.0032 | 8.99 | 663 | 0.0656 | 0.9885 |
| 0.0032 | 9.9 | 730 | 0.0657 | 0.9885 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3