metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: deit-tiny-patch16-224-finetuned-main-gpu-20e-final
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9856292517006803
deit-tiny-patch16-224-finetuned-main-gpu-20e-final
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0420
- Accuracy: 0.9856
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6047 | 1.0 | 551 | 0.6283 | 0.7111 |
| 0.431 | 2.0 | 1102 | 0.3962 | 0.8366 |
| 0.352 | 3.0 | 1653 | 0.2620 | 0.8953 |
| 0.2682 | 4.0 | 2204 | 0.1814 | 0.9318 |
| 0.2533 | 5.0 | 2755 | 0.1564 | 0.9396 |
| 0.2069 | 6.0 | 3306 | 0.1243 | 0.9531 |
| 0.2065 | 7.0 | 3857 | 0.1048 | 0.9603 |
| 0.194 | 8.0 | 4408 | 0.1019 | 0.9636 |
| 0.1879 | 9.0 | 4959 | 0.0877 | 0.9671 |
| 0.1584 | 10.0 | 5510 | 0.0870 | 0.9687 |
| 0.1426 | 11.0 | 6061 | 0.0814 | 0.9718 |
| 0.1596 | 12.0 | 6612 | 0.0740 | 0.9749 |
| 0.1125 | 13.0 | 7163 | 0.0613 | 0.9781 |
| 0.1374 | 14.0 | 7714 | 0.0570 | 0.9787 |
| 0.1003 | 15.0 | 8265 | 0.0596 | 0.9793 |
| 0.109 | 16.0 | 8816 | 0.0511 | 0.9815 |
| 0.1206 | 17.0 | 9367 | 0.0497 | 0.9829 |
| 0.1024 | 18.0 | 9918 | 0.0437 | 0.9844 |
| 0.1051 | 19.0 | 10469 | 0.0420 | 0.9851 |
| 0.0955 | 20.0 | 11020 | 0.0420 | 0.9856 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2