|
--- |
|
license: apache-2.0 |
|
base_model: facebook/deit-tiny-patch16-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: hushem_conflu_deneme_fold3 |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: test |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.627906976744186 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# hushem_conflu_deneme_fold3 |
|
|
|
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9617 |
|
- Accuracy: 0.6279 |
|
|
|
## 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: 0.001 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 6 | 1.6871 | 0.2558 | |
|
| 1.9835 | 2.0 | 12 | 1.3632 | 0.2326 | |
|
| 1.9835 | 3.0 | 18 | 1.4109 | 0.3256 | |
|
| 1.294 | 4.0 | 24 | 1.3794 | 0.4186 | |
|
| 1.2341 | 5.0 | 30 | 1.2119 | 0.4651 | |
|
| 1.2341 | 6.0 | 36 | 1.4964 | 0.4419 | |
|
| 1.0897 | 7.0 | 42 | 1.2398 | 0.4651 | |
|
| 1.0897 | 8.0 | 48 | 1.0532 | 0.5349 | |
|
| 0.9835 | 9.0 | 54 | 1.1022 | 0.5116 | |
|
| 0.9034 | 10.0 | 60 | 0.9784 | 0.6279 | |
|
| 0.9034 | 11.0 | 66 | 1.5952 | 0.5116 | |
|
| 0.8061 | 12.0 | 72 | 0.9828 | 0.5581 | |
|
| 0.8061 | 13.0 | 78 | 0.9199 | 0.7209 | |
|
| 0.765 | 14.0 | 84 | 1.0672 | 0.5581 | |
|
| 0.6513 | 15.0 | 90 | 1.0129 | 0.6744 | |
|
| 0.6513 | 16.0 | 96 | 0.9247 | 0.6977 | |
|
| 0.4919 | 17.0 | 102 | 0.9617 | 0.6279 | |
|
| 0.4919 | 18.0 | 108 | 0.9617 | 0.6279 | |
|
| 0.4742 | 19.0 | 114 | 0.9617 | 0.6279 | |
|
| 0.4695 | 20.0 | 120 | 0.9617 | 0.6279 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
