metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: attraction-classifier
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: 0.8252212389380531
attraction-classifier
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: 0.5421
- Accuracy: 0.8252
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: 16
- eval_batch_size: 16
- seed: 69
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5852 | 0.59 | 150 | 0.5592 | 0.7035 |
| 0.6115 | 1.18 | 300 | 0.6364 | 0.6704 |
| 0.475 | 1.77 | 450 | 0.5351 | 0.7257 |
| 0.4268 | 2.36 | 600 | 0.5552 | 0.7190 |
| 0.4349 | 2.95 | 750 | 0.4939 | 0.7677 |
| 0.364 | 3.54 | 900 | 0.4969 | 0.7611 |
| 0.343 | 4.13 | 1050 | 0.5717 | 0.7721 |
| 0.3516 | 4.72 | 1200 | 0.4815 | 0.7898 |
| 0.3222 | 5.31 | 1350 | 0.4609 | 0.8142 |
| 0.2444 | 5.91 | 1500 | 0.5285 | 0.7854 |
| 0.2152 | 6.5 | 1650 | 0.4901 | 0.8097 |
| 0.2318 | 7.09 | 1800 | 0.4804 | 0.8252 |
| 0.1875 | 7.68 | 1950 | 0.5690 | 0.8119 |
| 0.195 | 8.27 | 2100 | 0.5276 | 0.8031 |
| 0.1409 | 8.86 | 2250 | 0.5421 | 0.8252 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0