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_0001_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: 0.9024390243902439
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hushem_5x_deit_base_adamax_0001_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: 0.4553
- Accuracy: 0.9024

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7557        | 1.0   | 28   | 0.4830          | 0.7805   |
| 0.1392        | 2.0   | 56   | 0.3138          | 0.8293   |
| 0.0115        | 3.0   | 84   | 0.3481          | 0.8537   |
| 0.0078        | 4.0   | 112  | 0.3098          | 0.8537   |
| 0.0013        | 5.0   | 140  | 0.3283          | 0.9024   |
| 0.0023        | 6.0   | 168  | 0.5654          | 0.8537   |
| 0.0004        | 7.0   | 196  | 0.4129          | 0.9024   |
| 0.0003        | 8.0   | 224  | 0.4041          | 0.9024   |
| 0.0002        | 9.0   | 252  | 0.4192          | 0.9024   |
| 0.0002        | 10.0  | 280  | 0.4257          | 0.9024   |
| 0.0002        | 11.0  | 308  | 0.4271          | 0.9024   |
| 0.0002        | 12.0  | 336  | 0.4272          | 0.9024   |
| 0.0001        | 13.0  | 364  | 0.4303          | 0.9024   |
| 0.0002        | 14.0  | 392  | 0.4309          | 0.9024   |
| 0.0001        | 15.0  | 420  | 0.4302          | 0.9024   |
| 0.0001        | 16.0  | 448  | 0.4300          | 0.9024   |
| 0.0001        | 17.0  | 476  | 0.4319          | 0.9024   |
| 0.0001        | 18.0  | 504  | 0.4342          | 0.9024   |
| 0.0001        | 19.0  | 532  | 0.4349          | 0.9024   |
| 0.0001        | 20.0  | 560  | 0.4354          | 0.9024   |
| 0.0001        | 21.0  | 588  | 0.4378          | 0.9024   |
| 0.0001        | 22.0  | 616  | 0.4393          | 0.9024   |
| 0.0001        | 23.0  | 644  | 0.4414          | 0.9024   |
| 0.0001        | 24.0  | 672  | 0.4417          | 0.9024   |
| 0.0001        | 25.0  | 700  | 0.4428          | 0.9024   |
| 0.0001        | 26.0  | 728  | 0.4429          | 0.9024   |
| 0.0001        | 27.0  | 756  | 0.4437          | 0.9024   |
| 0.0001        | 28.0  | 784  | 0.4437          | 0.9024   |
| 0.0001        | 29.0  | 812  | 0.4449          | 0.9024   |
| 0.0001        | 30.0  | 840  | 0.4459          | 0.9024   |
| 0.0001        | 31.0  | 868  | 0.4470          | 0.9024   |
| 0.0001        | 32.0  | 896  | 0.4471          | 0.9024   |
| 0.0001        | 33.0  | 924  | 0.4499          | 0.9024   |
| 0.0001        | 34.0  | 952  | 0.4499          | 0.9024   |
| 0.0001        | 35.0  | 980  | 0.4504          | 0.9024   |
| 0.0001        | 36.0  | 1008 | 0.4504          | 0.9024   |
| 0.0001        | 37.0  | 1036 | 0.4513          | 0.9024   |
| 0.0001        | 38.0  | 1064 | 0.4525          | 0.9024   |
| 0.0001        | 39.0  | 1092 | 0.4530          | 0.9024   |
| 0.0001        | 40.0  | 1120 | 0.4533          | 0.9024   |
| 0.0001        | 41.0  | 1148 | 0.4538          | 0.9024   |
| 0.0001        | 42.0  | 1176 | 0.4539          | 0.9024   |
| 0.0001        | 43.0  | 1204 | 0.4547          | 0.9024   |
| 0.0001        | 44.0  | 1232 | 0.4551          | 0.9024   |
| 0.0001        | 45.0  | 1260 | 0.4551          | 0.9024   |
| 0.0001        | 46.0  | 1288 | 0.4551          | 0.9024   |
| 0.0001        | 47.0  | 1316 | 0.4553          | 0.9024   |
| 0.0001        | 48.0  | 1344 | 0.4553          | 0.9024   |
| 0.0001        | 49.0  | 1372 | 0.4553          | 0.9024   |
| 0.0001        | 50.0  | 1400 | 0.4553          | 0.9024   |


### Framework versions

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