transformers pytorch 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_40x_deit_base_sgd_00001_fold3
  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: 0.23255813953488372
---

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# hushem_40x_deit_base_sgd_00001_fold3

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: 1.4462
- Accuracy: 0.2326

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.395         | 1.0   | 217   | 1.4656          | 0.2326   |
| 1.3668        | 2.0   | 434   | 1.4647          | 0.2326   |
| 1.3731        | 3.0   | 651   | 1.4638          | 0.2326   |
| 1.4025        | 4.0   | 868   | 1.4629          | 0.2326   |
| 1.3639        | 5.0   | 1085  | 1.4620          | 0.2326   |
| 1.3879        | 6.0   | 1302  | 1.4612          | 0.2326   |
| 1.3778        | 7.0   | 1519  | 1.4604          | 0.2326   |
| 1.3612        | 8.0   | 1736  | 1.4596          | 0.2326   |
| 1.3705        | 9.0   | 1953  | 1.4589          | 0.2326   |
| 1.3789        | 10.0  | 2170  | 1.4582          | 0.2326   |
| 1.361         | 11.0  | 2387  | 1.4575          | 0.2326   |
| 1.3859        | 12.0  | 2604  | 1.4568          | 0.2326   |
| 1.3896        | 13.0  | 2821  | 1.4562          | 0.2326   |
| 1.3672        | 14.0  | 3038  | 1.4556          | 0.2326   |
| 1.3726        | 15.0  | 3255  | 1.4550          | 0.2326   |
| 1.3714        | 16.0  | 3472  | 1.4544          | 0.2326   |
| 1.3679        | 17.0  | 3689  | 1.4539          | 0.2326   |
| 1.3686        | 18.0  | 3906  | 1.4533          | 0.2326   |
| 1.3759        | 19.0  | 4123  | 1.4528          | 0.2326   |
| 1.3715        | 20.0  | 4340  | 1.4524          | 0.2326   |
| 1.3586        | 21.0  | 4557  | 1.4519          | 0.2326   |
| 1.3602        | 22.0  | 4774  | 1.4515          | 0.2326   |
| 1.3784        | 23.0  | 4991  | 1.4511          | 0.2326   |
| 1.3361        | 24.0  | 5208  | 1.4507          | 0.2326   |
| 1.3639        | 25.0  | 5425  | 1.4503          | 0.2326   |
| 1.3719        | 26.0  | 5642  | 1.4499          | 0.2326   |
| 1.37          | 27.0  | 5859  | 1.4496          | 0.2326   |
| 1.3566        | 28.0  | 6076  | 1.4493          | 0.2326   |
| 1.3167        | 29.0  | 6293  | 1.4490          | 0.2326   |
| 1.3522        | 30.0  | 6510  | 1.4487          | 0.2326   |
| 1.3828        | 31.0  | 6727  | 1.4484          | 0.2326   |
| 1.3664        | 32.0  | 6944  | 1.4481          | 0.2326   |
| 1.3407        | 33.0  | 7161  | 1.4479          | 0.2326   |
| 1.3633        | 34.0  | 7378  | 1.4477          | 0.2326   |
| 1.3611        | 35.0  | 7595  | 1.4475          | 0.2326   |
| 1.3425        | 36.0  | 7812  | 1.4473          | 0.2326   |
| 1.3418        | 37.0  | 8029  | 1.4471          | 0.2326   |
| 1.3479        | 38.0  | 8246  | 1.4470          | 0.2326   |
| 1.3576        | 39.0  | 8463  | 1.4468          | 0.2326   |
| 1.3408        | 40.0  | 8680  | 1.4467          | 0.2326   |
| 1.3433        | 41.0  | 8897  | 1.4466          | 0.2326   |
| 1.3828        | 42.0  | 9114  | 1.4465          | 0.2326   |
| 1.3558        | 43.0  | 9331  | 1.4464          | 0.2326   |
| 1.3616        | 44.0  | 9548  | 1.4463          | 0.2326   |
| 1.36          | 45.0  | 9765  | 1.4463          | 0.2326   |
| 1.3465        | 46.0  | 9982  | 1.4462          | 0.2326   |
| 1.3484        | 47.0  | 10199 | 1.4462          | 0.2326   |
| 1.3826        | 48.0  | 10416 | 1.4462          | 0.2326   |
| 1.3656        | 49.0  | 10633 | 1.4462          | 0.2326   |
| 1.3363        | 50.0  | 10850 | 1.4462          | 0.2326   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
