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---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_base_adamax_001_fold2
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: 0.6
---
<!-- 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_base_adamax_001_fold2
This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co./facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6061
- Accuracy: 0.6
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 6 | 1.4006 | 0.4667 |
| 2.0073 | 2.0 | 12 | 1.4185 | 0.2444 |
| 2.0073 | 3.0 | 18 | 1.8021 | 0.2444 |
| 1.3793 | 4.0 | 24 | 1.3019 | 0.2889 |
| 1.3619 | 5.0 | 30 | 1.2559 | 0.4222 |
| 1.3619 | 6.0 | 36 | 1.3762 | 0.3556 |
| 1.2354 | 7.0 | 42 | 1.1026 | 0.5333 |
| 1.2354 | 8.0 | 48 | 1.3770 | 0.3556 |
| 1.116 | 9.0 | 54 | 1.3199 | 0.3333 |
| 1.2825 | 10.0 | 60 | 1.2535 | 0.4444 |
| 1.2825 | 11.0 | 66 | 0.9621 | 0.5333 |
| 1.0651 | 12.0 | 72 | 1.0556 | 0.5778 |
| 1.0651 | 13.0 | 78 | 1.1244 | 0.4889 |
| 0.8879 | 14.0 | 84 | 1.1678 | 0.4889 |
| 0.7249 | 15.0 | 90 | 1.1215 | 0.5778 |
| 0.7249 | 16.0 | 96 | 1.2306 | 0.5333 |
| 0.5807 | 17.0 | 102 | 1.9201 | 0.5333 |
| 0.5807 | 18.0 | 108 | 2.0291 | 0.4667 |
| 0.5755 | 19.0 | 114 | 2.7334 | 0.5333 |
| 0.7966 | 20.0 | 120 | 1.6804 | 0.5111 |
| 0.7966 | 21.0 | 126 | 2.2911 | 0.4444 |
| 0.7407 | 22.0 | 132 | 1.3830 | 0.5333 |
| 0.7407 | 23.0 | 138 | 1.5155 | 0.5556 |
| 0.3047 | 24.0 | 144 | 1.6845 | 0.4889 |
| 0.2535 | 25.0 | 150 | 1.8110 | 0.4889 |
| 0.2535 | 26.0 | 156 | 1.9764 | 0.5111 |
| 0.4369 | 27.0 | 162 | 1.6350 | 0.4889 |
| 0.4369 | 28.0 | 168 | 2.4101 | 0.5111 |
| 0.2888 | 29.0 | 174 | 2.3032 | 0.4889 |
| 0.3277 | 30.0 | 180 | 1.7523 | 0.5556 |
| 0.3277 | 31.0 | 186 | 1.6541 | 0.6 |
| 0.1303 | 32.0 | 192 | 2.1471 | 0.5333 |
| 0.1303 | 33.0 | 198 | 2.1714 | 0.5556 |
| 0.0771 | 34.0 | 204 | 2.1399 | 0.5778 |
| 0.0588 | 35.0 | 210 | 2.1914 | 0.5778 |
| 0.0588 | 36.0 | 216 | 2.2720 | 0.5778 |
| 0.0221 | 37.0 | 222 | 2.4076 | 0.5778 |
| 0.0221 | 38.0 | 228 | 2.4716 | 0.5556 |
| 0.0111 | 39.0 | 234 | 2.5364 | 0.5556 |
| 0.0075 | 40.0 | 240 | 2.5792 | 0.6 |
| 0.0075 | 41.0 | 246 | 2.6027 | 0.6 |
| 0.0045 | 42.0 | 252 | 2.6061 | 0.6 |
| 0.0045 | 43.0 | 258 | 2.6061 | 0.6 |
| 0.003 | 44.0 | 264 | 2.6061 | 0.6 |
| 0.0047 | 45.0 | 270 | 2.6061 | 0.6 |
| 0.0047 | 46.0 | 276 | 2.6061 | 0.6 |
| 0.0042 | 47.0 | 282 | 2.6061 | 0.6 |
| 0.0042 | 48.0 | 288 | 2.6061 | 0.6 |
| 0.0037 | 49.0 | 294 | 2.6061 | 0.6 |
| 0.0043 | 50.0 | 300 | 2.6061 | 0.6 |
### Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
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