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: smids_5x_deit_base_sgd_001_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: 0.8683333333333333
---

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# smids_5x_deit_base_sgd_001_fold4

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: 0.3268
- Accuracy: 0.8683

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8132        | 1.0   | 375   | 0.8089          | 0.7267   |
| 0.5876        | 2.0   | 750   | 0.5635          | 0.8067   |
| 0.4083        | 3.0   | 1125  | 0.4614          | 0.8267   |
| 0.4267        | 4.0   | 1500  | 0.4160          | 0.8333   |
| 0.3511        | 5.0   | 1875  | 0.3904          | 0.845    |
| 0.2917        | 6.0   | 2250  | 0.3744          | 0.85     |
| 0.3158        | 7.0   | 2625  | 0.3647          | 0.8583   |
| 0.2749        | 8.0   | 3000  | 0.3555          | 0.86     |
| 0.3058        | 9.0   | 3375  | 0.3495          | 0.8583   |
| 0.2616        | 10.0  | 3750  | 0.3455          | 0.8667   |
| 0.2281        | 11.0  | 4125  | 0.3414          | 0.8683   |
| 0.2203        | 12.0  | 4500  | 0.3404          | 0.87     |
| 0.1983        | 13.0  | 4875  | 0.3366          | 0.8733   |
| 0.2917        | 14.0  | 5250  | 0.3335          | 0.875    |
| 0.2068        | 15.0  | 5625  | 0.3331          | 0.8767   |
| 0.1668        | 16.0  | 6000  | 0.3311          | 0.8767   |
| 0.2429        | 17.0  | 6375  | 0.3309          | 0.88     |
| 0.2255        | 18.0  | 6750  | 0.3295          | 0.8817   |
| 0.217         | 19.0  | 7125  | 0.3289          | 0.88     |
| 0.1858        | 20.0  | 7500  | 0.3267          | 0.875    |
| 0.1989        | 21.0  | 7875  | 0.3279          | 0.875    |
| 0.1971        | 22.0  | 8250  | 0.3262          | 0.8767   |
| 0.1898        | 23.0  | 8625  | 0.3266          | 0.875    |
| 0.1832        | 24.0  | 9000  | 0.3251          | 0.8767   |
| 0.2234        | 25.0  | 9375  | 0.3260          | 0.875    |
| 0.1745        | 26.0  | 9750  | 0.3248          | 0.8767   |
| 0.2157        | 27.0  | 10125 | 0.3261          | 0.875    |
| 0.1917        | 28.0  | 10500 | 0.3254          | 0.8717   |
| 0.169         | 29.0  | 10875 | 0.3264          | 0.87     |
| 0.238         | 30.0  | 11250 | 0.3268          | 0.8683   |
| 0.1975        | 31.0  | 11625 | 0.3288          | 0.87     |
| 0.139         | 32.0  | 12000 | 0.3247          | 0.8717   |
| 0.1975        | 33.0  | 12375 | 0.3257          | 0.8683   |
| 0.1914        | 34.0  | 12750 | 0.3239          | 0.875    |
| 0.1455        | 35.0  | 13125 | 0.3252          | 0.8717   |
| 0.1611        | 36.0  | 13500 | 0.3266          | 0.8683   |
| 0.2074        | 37.0  | 13875 | 0.3252          | 0.8767   |
| 0.1665        | 38.0  | 14250 | 0.3262          | 0.8683   |
| 0.2306        | 39.0  | 14625 | 0.3258          | 0.8683   |
| 0.1821        | 40.0  | 15000 | 0.3259          | 0.8683   |
| 0.154         | 41.0  | 15375 | 0.3262          | 0.8683   |
| 0.1817        | 42.0  | 15750 | 0.3261          | 0.8683   |
| 0.2063        | 43.0  | 16125 | 0.3258          | 0.8717   |
| 0.1391        | 44.0  | 16500 | 0.3266          | 0.8683   |
| 0.2228        | 45.0  | 16875 | 0.3270          | 0.8683   |
| 0.1476        | 46.0  | 17250 | 0.3269          | 0.87     |
| 0.2362        | 47.0  | 17625 | 0.3264          | 0.8683   |
| 0.1702        | 48.0  | 18000 | 0.3268          | 0.8683   |
| 0.1619        | 49.0  | 18375 | 0.3268          | 0.8683   |
| 0.1838        | 50.0  | 18750 | 0.3268          | 0.8683   |


### Framework versions

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