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: 0.777292576419214
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: 0.5411
- Accuracy: 0.7773
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 |
|---|---|---|---|---|
| 0.5969 | 0.58 | 150 | 0.5433 | 0.7227 |
| 0.5066 | 1.16 | 300 | 0.5094 | 0.7402 |
| 0.4708 | 1.74 | 450 | 0.5290 | 0.7227 |
| 0.4099 | 2.33 | 600 | 0.4632 | 0.7904 |
| 0.4078 | 2.91 | 750 | 0.4827 | 0.7751 |
| 0.3681 | 3.49 | 900 | 0.4536 | 0.7969 |
| 0.3318 | 4.07 | 1050 | 0.4662 | 0.7838 |
| 0.3329 | 4.65 | 1200 | 0.4802 | 0.7948 |
| 0.2758 | 5.23 | 1350 | 0.5411 | 0.7773 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0