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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_fold4
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: 0.7380952380952381
---
<!-- 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_fold4
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: 0.8165
- Accuracy: 0.7381
## 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 | 1.7088 | 0.2381 |
| 1.9076 | 2.0 | 12 | 1.4617 | 0.2381 |
| 1.9076 | 3.0 | 18 | 1.4512 | 0.2619 |
| 1.4689 | 4.0 | 24 | 1.3283 | 0.2381 |
| 1.3599 | 5.0 | 30 | 1.0112 | 0.6667 |
| 1.3599 | 6.0 | 36 | 1.1598 | 0.3810 |
| 1.2233 | 7.0 | 42 | 1.4323 | 0.4524 |
| 1.2233 | 8.0 | 48 | 0.9658 | 0.6667 |
| 1.0502 | 9.0 | 54 | 0.9166 | 0.6429 |
| 0.8636 | 10.0 | 60 | 0.8181 | 0.6190 |
| 0.8636 | 11.0 | 66 | 1.2729 | 0.5238 |
| 0.8856 | 12.0 | 72 | 0.7434 | 0.7381 |
| 0.8856 | 13.0 | 78 | 0.6840 | 0.7143 |
| 0.6672 | 14.0 | 84 | 0.9596 | 0.5238 |
| 0.5861 | 15.0 | 90 | 0.7243 | 0.7381 |
| 0.5861 | 16.0 | 96 | 0.8378 | 0.7143 |
| 0.4357 | 17.0 | 102 | 0.8165 | 0.7381 |
| 0.4357 | 18.0 | 108 | 0.8165 | 0.7381 |
| 0.4614 | 19.0 | 114 | 0.8165 | 0.7381 |
| 0.431 | 20.0 | 120 | 0.8165 | 0.7381 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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