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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_1x_deit_tiny_rms_00001_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: 0.8571428571428571
---
<!-- 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_1x_deit_tiny_rms_00001_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: 0.4549
- Accuracy: 0.8571
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 6 | 1.4075 | 0.2857 |
| 1.4145 | 2.0 | 12 | 1.3443 | 0.3571 |
| 1.4145 | 3.0 | 18 | 0.8612 | 0.6667 |
| 0.7818 | 4.0 | 24 | 0.9127 | 0.6190 |
| 0.3833 | 5.0 | 30 | 0.5998 | 0.8810 |
| 0.3833 | 6.0 | 36 | 0.5796 | 0.7857 |
| 0.1457 | 7.0 | 42 | 0.5756 | 0.8333 |
| 0.1457 | 8.0 | 48 | 0.5188 | 0.7857 |
| 0.0559 | 9.0 | 54 | 0.5146 | 0.8571 |
| 0.0198 | 10.0 | 60 | 0.5290 | 0.7857 |
| 0.0198 | 11.0 | 66 | 0.4513 | 0.8571 |
| 0.007 | 12.0 | 72 | 0.4696 | 0.8571 |
| 0.007 | 13.0 | 78 | 0.4668 | 0.8333 |
| 0.0039 | 14.0 | 84 | 0.4642 | 0.8333 |
| 0.0028 | 15.0 | 90 | 0.4519 | 0.8571 |
| 0.0028 | 16.0 | 96 | 0.4562 | 0.8333 |
| 0.0022 | 17.0 | 102 | 0.4543 | 0.8571 |
| 0.0022 | 18.0 | 108 | 0.4588 | 0.8571 |
| 0.0018 | 19.0 | 114 | 0.4546 | 0.8571 |
| 0.0016 | 20.0 | 120 | 0.4551 | 0.8333 |
| 0.0016 | 21.0 | 126 | 0.4570 | 0.8333 |
| 0.0013 | 22.0 | 132 | 0.4556 | 0.8333 |
| 0.0013 | 23.0 | 138 | 0.4547 | 0.8333 |
| 0.0012 | 24.0 | 144 | 0.4556 | 0.8571 |
| 0.0011 | 25.0 | 150 | 0.4547 | 0.8571 |
| 0.0011 | 26.0 | 156 | 0.4538 | 0.8571 |
| 0.001 | 27.0 | 162 | 0.4593 | 0.8333 |
| 0.001 | 28.0 | 168 | 0.4560 | 0.8333 |
| 0.0009 | 29.0 | 174 | 0.4555 | 0.8333 |
| 0.0009 | 30.0 | 180 | 0.4554 | 0.8333 |
| 0.0009 | 31.0 | 186 | 0.4563 | 0.8333 |
| 0.0008 | 32.0 | 192 | 0.4547 | 0.8571 |
| 0.0008 | 33.0 | 198 | 0.4545 | 0.8571 |
| 0.0008 | 34.0 | 204 | 0.4547 | 0.8571 |
| 0.0007 | 35.0 | 210 | 0.4541 | 0.8571 |
| 0.0007 | 36.0 | 216 | 0.4545 | 0.8571 |
| 0.0007 | 37.0 | 222 | 0.4550 | 0.8571 |
| 0.0007 | 38.0 | 228 | 0.4547 | 0.8571 |
| 0.0007 | 39.0 | 234 | 0.4549 | 0.8571 |
| 0.0007 | 40.0 | 240 | 0.4549 | 0.8571 |
| 0.0007 | 41.0 | 246 | 0.4549 | 0.8571 |
| 0.0007 | 42.0 | 252 | 0.4549 | 0.8571 |
| 0.0007 | 43.0 | 258 | 0.4549 | 0.8571 |
| 0.0007 | 44.0 | 264 | 0.4549 | 0.8571 |
| 0.0007 | 45.0 | 270 | 0.4549 | 0.8571 |
| 0.0007 | 46.0 | 276 | 0.4549 | 0.8571 |
| 0.0007 | 47.0 | 282 | 0.4549 | 0.8571 |
| 0.0007 | 48.0 | 288 | 0.4549 | 0.8571 |
| 0.0007 | 49.0 | 294 | 0.4549 | 0.8571 |
| 0.0007 | 50.0 | 300 | 0.4549 | 0.8571 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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