transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_base_adamax_00001_fold5
  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: 0.8780487804878049
---

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# hushem_5x_deit_base_adamax_00001_fold5

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: 0.5126
- Accuracy: 0.8780

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2842        | 1.0   | 28   | 1.2327          | 0.4634   |
| 1.0428        | 2.0   | 56   | 1.0859          | 0.5854   |
| 0.7338        | 3.0   | 84   | 0.9001          | 0.6585   |
| 0.526         | 4.0   | 112  | 0.7803          | 0.6829   |
| 0.3644        | 5.0   | 140  | 0.6952          | 0.6829   |
| 0.2797        | 6.0   | 168  | 0.5854          | 0.7073   |
| 0.1574        | 7.0   | 196  | 0.5546          | 0.7561   |
| 0.1102        | 8.0   | 224  | 0.5073          | 0.7805   |
| 0.0668        | 9.0   | 252  | 0.4703          | 0.8049   |
| 0.0352        | 10.0  | 280  | 0.4612          | 0.8293   |
| 0.0202        | 11.0  | 308  | 0.4468          | 0.8537   |
| 0.0126        | 12.0  | 336  | 0.4508          | 0.8537   |
| 0.0083        | 13.0  | 364  | 0.4495          | 0.8537   |
| 0.0078        | 14.0  | 392  | 0.4584          | 0.8780   |
| 0.0058        | 15.0  | 420  | 0.4565          | 0.8537   |
| 0.0051        | 16.0  | 448  | 0.4617          | 0.8780   |
| 0.0041        | 17.0  | 476  | 0.4620          | 0.8537   |
| 0.0038        | 18.0  | 504  | 0.4684          | 0.8780   |
| 0.0035        | 19.0  | 532  | 0.4714          | 0.8780   |
| 0.0033        | 20.0  | 560  | 0.4764          | 0.8780   |
| 0.0027        | 21.0  | 588  | 0.4824          | 0.8780   |
| 0.0027        | 22.0  | 616  | 0.4828          | 0.8780   |
| 0.0023        | 23.0  | 644  | 0.4858          | 0.8780   |
| 0.0021        | 24.0  | 672  | 0.4874          | 0.8780   |
| 0.002         | 25.0  | 700  | 0.4903          | 0.8780   |
| 0.002         | 26.0  | 728  | 0.4912          | 0.8780   |
| 0.0019        | 27.0  | 756  | 0.4926          | 0.8780   |
| 0.0017        | 28.0  | 784  | 0.4940          | 0.8780   |
| 0.0016        | 29.0  | 812  | 0.4962          | 0.8780   |
| 0.0016        | 30.0  | 840  | 0.4964          | 0.8780   |
| 0.0015        | 31.0  | 868  | 0.4991          | 0.8780   |
| 0.0015        | 32.0  | 896  | 0.5002          | 0.8780   |
| 0.0013        | 33.0  | 924  | 0.5024          | 0.8780   |
| 0.0014        | 34.0  | 952  | 0.5035          | 0.8780   |
| 0.0013        | 35.0  | 980  | 0.5045          | 0.8780   |
| 0.0013        | 36.0  | 1008 | 0.5049          | 0.8780   |
| 0.0012        | 37.0  | 1036 | 0.5067          | 0.8780   |
| 0.0012        | 38.0  | 1064 | 0.5085          | 0.8780   |
| 0.0012        | 39.0  | 1092 | 0.5083          | 0.8780   |
| 0.0011        | 40.0  | 1120 | 0.5095          | 0.8780   |
| 0.0011        | 41.0  | 1148 | 0.5101          | 0.8780   |
| 0.0011        | 42.0  | 1176 | 0.5103          | 0.8780   |
| 0.0011        | 43.0  | 1204 | 0.5116          | 0.8780   |
| 0.0011        | 44.0  | 1232 | 0.5122          | 0.8780   |
| 0.0011        | 45.0  | 1260 | 0.5120          | 0.8780   |
| 0.0011        | 46.0  | 1288 | 0.5123          | 0.8780   |
| 0.001         | 47.0  | 1316 | 0.5124          | 0.8780   |
| 0.0011        | 48.0  | 1344 | 0.5126          | 0.8780   |
| 0.001         | 49.0  | 1372 | 0.5126          | 0.8780   |
| 0.0011        | 50.0  | 1400 | 0.5126          | 0.8780   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
