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: 0.8389955686853766
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: 0.3983
- Accuracy: 0.8390
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: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
---|---|---|---|---|
0.5745 | 0.99 | 42 | 0.5208 | 0.7829 |
0.4617 | 2.0 | 85 | 0.4346 | 0.8065 |
0.4245 | 2.99 | 127 | 0.4151 | 0.8346 |
0.3512 | 4.0 | 170 | 0.3854 | 0.8508 |
0.3146 | 4.99 | 212 | 0.4062 | 0.8360 |
0.3235 | 6.0 | 255 | 0.3864 | 0.8390 |
0.2699 | 6.99 | 297 | 0.4094 | 0.8508 |
0.3049 | 8.0 | 340 | 0.3735 | 0.8567 |
0.2459 | 8.99 | 382 | 0.4037 | 0.8360 |
0.2277 | 9.88 | 420 | 0.3983 | 0.8390 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0