metadata
license: apache-2.0
base_model: google/vit-huge-patch14-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: fashion-images-pack-types-vit-huge-patch14-224-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: 0.989010989010989
fashion-images-pack-types-vit-huge-patch14-224-in21k
This model is a fine-tuned version of google/vit-huge-patch14-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0436
- Accuracy: 0.9890
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 |
---|---|---|---|---|
0.2292 | 1.0 | 1676 | 0.1293 | 0.9755 |
0.1376 | 2.0 | 3352 | 0.0769 | 0.9827 |
0.1122 | 3.0 | 5028 | 0.0565 | 0.9852 |
0.0759 | 4.0 | 6704 | 0.0501 | 0.9873 |
0.0678 | 5.0 | 8380 | 0.0436 | 0.9890 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3