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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_40x_deit_tiny_sgd_00001_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: 0.28888888888888886
---
<!-- 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_40x_deit_tiny_sgd_00001_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: 1.3702
- Accuracy: 0.2889
## 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: 1e-05
- 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.5833 | 1.0 | 215 | 1.4002 | 0.1778 |
| 1.5381 | 2.0 | 430 | 1.3990 | 0.2 |
| 1.505 | 3.0 | 645 | 1.3978 | 0.2222 |
| 1.446 | 4.0 | 860 | 1.3967 | 0.2444 |
| 1.4742 | 5.0 | 1075 | 1.3956 | 0.2222 |
| 1.3991 | 6.0 | 1290 | 1.3945 | 0.2222 |
| 1.4142 | 7.0 | 1505 | 1.3933 | 0.2222 |
| 1.4895 | 8.0 | 1720 | 1.3923 | 0.2222 |
| 1.4297 | 9.0 | 1935 | 1.3912 | 0.2222 |
| 1.4803 | 10.0 | 2150 | 1.3901 | 0.2222 |
| 1.4253 | 11.0 | 2365 | 1.3890 | 0.2222 |
| 1.4151 | 12.0 | 2580 | 1.3880 | 0.2222 |
| 1.3649 | 13.0 | 2795 | 1.3870 | 0.2222 |
| 1.4058 | 14.0 | 3010 | 1.3860 | 0.2444 |
| 1.3858 | 15.0 | 3225 | 1.3850 | 0.2444 |
| 1.3985 | 16.0 | 3440 | 1.3841 | 0.2444 |
| 1.4078 | 17.0 | 3655 | 1.3832 | 0.2444 |
| 1.3916 | 18.0 | 3870 | 1.3823 | 0.2444 |
| 1.4138 | 19.0 | 4085 | 1.3814 | 0.2444 |
| 1.3697 | 20.0 | 4300 | 1.3807 | 0.2444 |
| 1.3976 | 21.0 | 4515 | 1.3799 | 0.2444 |
| 1.45 | 22.0 | 4730 | 1.3791 | 0.2444 |
| 1.3757 | 23.0 | 4945 | 1.3784 | 0.2444 |
| 1.4088 | 24.0 | 5160 | 1.3777 | 0.2667 |
| 1.3948 | 25.0 | 5375 | 1.3771 | 0.2667 |
| 1.3916 | 26.0 | 5590 | 1.3764 | 0.2667 |
| 1.3383 | 27.0 | 5805 | 1.3759 | 0.2667 |
| 1.3507 | 28.0 | 6020 | 1.3753 | 0.2889 |
| 1.3823 | 29.0 | 6235 | 1.3748 | 0.2889 |
| 1.3489 | 30.0 | 6450 | 1.3743 | 0.2889 |
| 1.3905 | 31.0 | 6665 | 1.3738 | 0.2889 |
| 1.3646 | 32.0 | 6880 | 1.3734 | 0.2889 |
| 1.394 | 33.0 | 7095 | 1.3730 | 0.2889 |
| 1.3256 | 34.0 | 7310 | 1.3726 | 0.2889 |
| 1.342 | 35.0 | 7525 | 1.3723 | 0.2889 |
| 1.3277 | 36.0 | 7740 | 1.3720 | 0.2889 |
| 1.3815 | 37.0 | 7955 | 1.3717 | 0.2889 |
| 1.3516 | 38.0 | 8170 | 1.3714 | 0.2889 |
| 1.3573 | 39.0 | 8385 | 1.3712 | 0.2889 |
| 1.3764 | 40.0 | 8600 | 1.3710 | 0.2889 |
| 1.3508 | 41.0 | 8815 | 1.3708 | 0.2889 |
| 1.4032 | 42.0 | 9030 | 1.3707 | 0.2889 |
| 1.3548 | 43.0 | 9245 | 1.3705 | 0.2889 |
| 1.3623 | 44.0 | 9460 | 1.3704 | 0.2889 |
| 1.3744 | 45.0 | 9675 | 1.3704 | 0.2889 |
| 1.3298 | 46.0 | 9890 | 1.3703 | 0.2889 |
| 1.352 | 47.0 | 10105 | 1.3703 | 0.2889 |
| 1.363 | 48.0 | 10320 | 1.3702 | 0.2889 |
| 1.3844 | 49.0 | 10535 | 1.3702 | 0.2889 |
| 1.3587 | 50.0 | 10750 | 1.3702 | 0.2889 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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