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---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_sgd_001_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: 0.7777777777777778
---
<!-- 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_small_sgd_001_fold1
This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6398
- Accuracy: 0.7778
## 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1952 | 1.0 | 215 | 1.4276 | 0.3778 |
| 1.0042 | 2.0 | 430 | 1.4162 | 0.2889 |
| 0.8488 | 3.0 | 645 | 1.3544 | 0.3778 |
| 0.7465 | 4.0 | 860 | 1.2674 | 0.4889 |
| 0.6036 | 5.0 | 1075 | 1.1735 | 0.5111 |
| 0.5355 | 6.0 | 1290 | 1.0934 | 0.5556 |
| 0.4712 | 7.0 | 1505 | 1.0208 | 0.6 |
| 0.3805 | 8.0 | 1720 | 0.9372 | 0.6222 |
| 0.3422 | 9.0 | 1935 | 0.8901 | 0.6444 |
| 0.2964 | 10.0 | 2150 | 0.8433 | 0.6667 |
| 0.2485 | 11.0 | 2365 | 0.7909 | 0.6889 |
| 0.2255 | 12.0 | 2580 | 0.7693 | 0.7111 |
| 0.1717 | 13.0 | 2795 | 0.7309 | 0.7556 |
| 0.1588 | 14.0 | 3010 | 0.7252 | 0.7556 |
| 0.1672 | 15.0 | 3225 | 0.6986 | 0.7333 |
| 0.1097 | 16.0 | 3440 | 0.6863 | 0.7333 |
| 0.1167 | 17.0 | 3655 | 0.6753 | 0.7556 |
| 0.0952 | 18.0 | 3870 | 0.6754 | 0.7556 |
| 0.0806 | 19.0 | 4085 | 0.6768 | 0.7556 |
| 0.0794 | 20.0 | 4300 | 0.6533 | 0.7556 |
| 0.0649 | 21.0 | 4515 | 0.6553 | 0.7556 |
| 0.0639 | 22.0 | 4730 | 0.6451 | 0.7556 |
| 0.0578 | 23.0 | 4945 | 0.6498 | 0.7556 |
| 0.0439 | 24.0 | 5160 | 0.6457 | 0.7556 |
| 0.0437 | 25.0 | 5375 | 0.6423 | 0.7556 |
| 0.038 | 26.0 | 5590 | 0.6342 | 0.7556 |
| 0.0346 | 27.0 | 5805 | 0.6184 | 0.7556 |
| 0.0278 | 28.0 | 6020 | 0.6299 | 0.7556 |
| 0.035 | 29.0 | 6235 | 0.6381 | 0.7556 |
| 0.0226 | 30.0 | 6450 | 0.6272 | 0.7556 |
| 0.0178 | 31.0 | 6665 | 0.6325 | 0.7556 |
| 0.019 | 32.0 | 6880 | 0.6409 | 0.7556 |
| 0.0184 | 33.0 | 7095 | 0.6323 | 0.7778 |
| 0.0238 | 34.0 | 7310 | 0.6091 | 0.7556 |
| 0.0126 | 35.0 | 7525 | 0.6363 | 0.7778 |
| 0.0156 | 36.0 | 7740 | 0.6253 | 0.7556 |
| 0.0165 | 37.0 | 7955 | 0.6280 | 0.7556 |
| 0.0106 | 38.0 | 8170 | 0.6294 | 0.7778 |
| 0.0189 | 39.0 | 8385 | 0.6262 | 0.7778 |
| 0.0098 | 40.0 | 8600 | 0.6454 | 0.7556 |
| 0.0098 | 41.0 | 8815 | 0.6342 | 0.7778 |
| 0.0112 | 42.0 | 9030 | 0.6356 | 0.7778 |
| 0.0128 | 43.0 | 9245 | 0.6416 | 0.7778 |
| 0.0115 | 44.0 | 9460 | 0.6374 | 0.7778 |
| 0.0087 | 45.0 | 9675 | 0.6423 | 0.7778 |
| 0.0077 | 46.0 | 9890 | 0.6446 | 0.7778 |
| 0.0087 | 47.0 | 10105 | 0.6388 | 0.7778 |
| 0.0071 | 48.0 | 10320 | 0.6394 | 0.7778 |
| 0.0087 | 49.0 | 10535 | 0.6404 | 0.7778 |
| 0.0108 | 50.0 | 10750 | 0.6398 | 0.7778 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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