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---
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_fold1
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: 0.5111111111111111
---
<!-- 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_fold1
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: 2.8961
- Accuracy: 0.5111
## 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 | 1.4190 | 0.2444 |
| 1.9213 | 2.0 | 12 | 1.3227 | 0.3111 |
| 1.9213 | 3.0 | 18 | 2.3526 | 0.2444 |
| 1.2734 | 4.0 | 24 | 1.7104 | 0.3778 |
| 1.0407 | 5.0 | 30 | 1.6039 | 0.3556 |
| 1.0407 | 6.0 | 36 | 1.2459 | 0.4667 |
| 0.733 | 7.0 | 42 | 1.3344 | 0.4667 |
| 0.733 | 8.0 | 48 | 1.5744 | 0.5556 |
| 0.448 | 9.0 | 54 | 1.2479 | 0.5556 |
| 0.3254 | 10.0 | 60 | 2.2545 | 0.5333 |
| 0.3254 | 11.0 | 66 | 1.7472 | 0.5333 |
| 0.2088 | 12.0 | 72 | 2.0350 | 0.5778 |
| 0.2088 | 13.0 | 78 | 3.0002 | 0.4889 |
| 0.1216 | 14.0 | 84 | 2.1774 | 0.5556 |
| 0.0746 | 15.0 | 90 | 2.5953 | 0.5333 |
| 0.0746 | 16.0 | 96 | 2.8934 | 0.5111 |
| 0.0176 | 17.0 | 102 | 2.8961 | 0.5111 |
| 0.0176 | 18.0 | 108 | 2.8961 | 0.5111 |
| 0.0201 | 19.0 | 114 | 2.8961 | 0.5111 |
| 0.0136 | 20.0 | 120 | 2.8961 | 0.5111 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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