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_001_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: 0.8048780487804879
---

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# hushem_40x_deit_base_sgd_001_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: 0.5235
- Accuracy: 0.8049

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2691        | 1.0   | 220   | 1.3176          | 0.3415   |
| 1.1324        | 2.0   | 440   | 1.2295          | 0.4634   |
| 1.003         | 3.0   | 660   | 1.1173          | 0.6341   |
| 0.8718        | 4.0   | 880   | 0.9888          | 0.6585   |
| 0.7662        | 5.0   | 1100  | 0.8700          | 0.6829   |
| 0.6305        | 6.0   | 1320  | 0.7780          | 0.6585   |
| 0.552         | 7.0   | 1540  | 0.7068          | 0.6829   |
| 0.4791        | 8.0   | 1760  | 0.6670          | 0.6829   |
| 0.413         | 9.0   | 1980  | 0.6302          | 0.6829   |
| 0.3827        | 10.0  | 2200  | 0.6050          | 0.7073   |
| 0.3215        | 11.0  | 2420  | 0.5880          | 0.7073   |
| 0.2953        | 12.0  | 2640  | 0.5689          | 0.7073   |
| 0.2691        | 13.0  | 2860  | 0.5551          | 0.7073   |
| 0.255         | 14.0  | 3080  | 0.5391          | 0.7317   |
| 0.2205        | 15.0  | 3300  | 0.5338          | 0.7561   |
| 0.2031        | 16.0  | 3520  | 0.5276          | 0.8049   |
| 0.1827        | 17.0  | 3740  | 0.5158          | 0.8049   |
| 0.178         | 18.0  | 3960  | 0.5117          | 0.8049   |
| 0.1722        | 19.0  | 4180  | 0.5070          | 0.8293   |
| 0.1354        | 20.0  | 4400  | 0.5054          | 0.8293   |
| 0.1154        | 21.0  | 4620  | 0.5008          | 0.8293   |
| 0.1032        | 22.0  | 4840  | 0.5031          | 0.8293   |
| 0.123         | 23.0  | 5060  | 0.5052          | 0.8293   |
| 0.0925        | 24.0  | 5280  | 0.5012          | 0.8049   |
| 0.1004        | 25.0  | 5500  | 0.5002          | 0.8293   |
| 0.1106        | 26.0  | 5720  | 0.5000          | 0.8293   |
| 0.0932        | 27.0  | 5940  | 0.5018          | 0.8293   |
| 0.0974        | 28.0  | 6160  | 0.5069          | 0.8293   |
| 0.0749        | 29.0  | 6380  | 0.5067          | 0.8293   |
| 0.0626        | 30.0  | 6600  | 0.5071          | 0.8293   |
| 0.058         | 31.0  | 6820  | 0.5023          | 0.8293   |
| 0.0771        | 32.0  | 7040  | 0.5068          | 0.8293   |
| 0.0537        | 33.0  | 7260  | 0.5089          | 0.8049   |
| 0.0443        | 34.0  | 7480  | 0.5110          | 0.8049   |
| 0.0529        | 35.0  | 7700  | 0.5102          | 0.8049   |
| 0.056         | 36.0  | 7920  | 0.5123          | 0.8293   |
| 0.0373        | 37.0  | 8140  | 0.5147          | 0.8293   |
| 0.0662        | 38.0  | 8360  | 0.5122          | 0.8293   |
| 0.0489        | 39.0  | 8580  | 0.5155          | 0.8293   |
| 0.0389        | 40.0  | 8800  | 0.5166          | 0.8293   |
| 0.0414        | 41.0  | 9020  | 0.5205          | 0.8049   |
| 0.0455        | 42.0  | 9240  | 0.5225          | 0.8293   |
| 0.0397        | 43.0  | 9460  | 0.5226          | 0.8049   |
| 0.0345        | 44.0  | 9680  | 0.5228          | 0.8049   |
| 0.0281        | 45.0  | 9900  | 0.5217          | 0.8049   |
| 0.0392        | 46.0  | 10120 | 0.5231          | 0.8049   |
| 0.0436        | 47.0  | 10340 | 0.5235          | 0.8293   |
| 0.0347        | 48.0  | 10560 | 0.5238          | 0.8049   |
| 0.0331        | 49.0  | 10780 | 0.5237          | 0.8049   |
| 0.0457        | 50.0  | 11000 | 0.5235          | 0.8049   |


### Framework versions

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