metadata
license: apache-2.0
base_model: google/vit-large-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: fashion-images-perspectives-vit-large-patch16-224-in21k
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: 0.936190032603633
fashion-images-perspectives-vit-large-patch16-224-in21k
This model is a fine-tuned version of google/vit-large-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2562
- Accuracy: 0.9362
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4164 | 1.0 | 3042 | 0.2868 | 0.9024 |
0.3391 | 2.0 | 6084 | 0.3055 | 0.9041 |
0.2836 | 3.0 | 9126 | 0.3071 | 0.9180 |
0.2292 | 4.0 | 12168 | 0.2543 | 0.9315 |
0.1842 | 5.0 | 15210 | 0.2562 | 0.9362 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3